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  • Looking for speech-to-text tool (convert .wav to text)

    - by David
    I have the ability to get .wav files of voice mails emailed to me, but sometimes I'll be sitting in a meeting and I need to know the content of a message without playing it out loud. Are there any good (and, preferably, free) tools for converting .wav files to text? I know Google Voice has this capability, but I can't determine if it'll work on a file-by-file basis. I realize that this is a difficult research problem, but even an 80% solution might be workable.

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  • Error in running script [closed]

    - by SWEngineer
    I'm trying to run heathusf_v1.1.0.tar.gz found here I installed tcsh to make build_heathusf work. But, when I run ./build_heathusf, I get the following (I'm running that on a Fedora Linux system from Terminal): $ ./build_heathusf Compiling programs to build a library of image processing functions. convexpolyscan.c: In function ‘cdelete’: convexpolyscan.c:346:5: warning: incompatible implicit declaration of built-in function ‘bcopy’ [enabled by default] myalloc.c: In function ‘mycalloc’: myalloc.c:68:16: error: invalid storage class for function ‘store_link’ myalloc.c: In function ‘mymalloc’: myalloc.c:101:16: error: invalid storage class for function ‘store_link’ myalloc.c: In function ‘myfree’: myalloc.c:129:27: error: invalid storage class for function ‘find_link’ myalloc.c:131:12: warning: assignment makes pointer from integer without a cast [enabled by default] myalloc.c: At top level: myalloc.c:150:13: warning: conflicting types for ‘store_link’ [enabled by default] myalloc.c:150:13: error: static declaration of ‘store_link’ follows non-static declaration myalloc.c:91:4: note: previous implicit declaration of ‘store_link’ was here myalloc.c:164:24: error: conflicting types for ‘find_link’ myalloc.c:131:14: note: previous implicit declaration of ‘find_link’ was here Building the mammogram resizing program. gcc -O2 -I. -I../common mkimage.o -o mkimage -L../common -lmammo -lm ../common/libmammo.a(aggregate.o): In function `aggregate': aggregate.c:(.text+0x7fa): undefined reference to `mycalloc' aggregate.c:(.text+0x81c): undefined reference to `mycalloc' aggregate.c:(.text+0x868): undefined reference to `mycalloc' ../common/libmammo.a(aggregate.o): In function `aggregate_median': aggregate.c:(.text+0xbc5): undefined reference to `mymalloc' aggregate.c:(.text+0xbfb): undefined reference to `mycalloc' aggregate.c:(.text+0xc3c): undefined reference to `mycalloc' ../common/libmammo.a(aggregate.o): In function `aggregate': aggregate.c:(.text+0x9b5): undefined reference to `myfree' ../common/libmammo.a(aggregate.o): In function `aggregate_median': aggregate.c:(.text+0xd85): undefined reference to `myfree' ../common/libmammo.a(optical_density.o): In function `linear_optical_density': optical_density.c:(.text+0x29e): undefined reference to `mymalloc' optical_density.c:(.text+0x342): undefined reference to `mycalloc' optical_density.c:(.text+0x383): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `log10_optical_density': optical_density.c:(.text+0x693): undefined reference to `mymalloc' optical_density.c:(.text+0x74f): undefined reference to `mycalloc' optical_density.c:(.text+0x790): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `map_with_ushort_lut': optical_density.c:(.text+0xb2e): undefined reference to `mymalloc' optical_density.c:(.text+0xb87): undefined reference to `mycalloc' optical_density.c:(.text+0xbc6): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `linear_optical_density': optical_density.c:(.text+0x4d9): undefined reference to `myfree' ../common/libmammo.a(optical_density.o): In function `log10_optical_density': optical_density.c:(.text+0x8f1): undefined reference to `myfree' ../common/libmammo.a(optical_density.o): In function `map_with_ushort_lut': optical_density.c:(.text+0xd0d): undefined reference to `myfree' ../common/libmammo.a(virtual_image.o): In function `deallocate_cached_image': virtual_image.c:(.text+0x3dc6): undefined reference to `myfree' virtual_image.c:(.text+0x3dd7): undefined reference to `myfree' ../common/libmammo.a(virtual_image.o):virtual_image.c:(.text+0x3de5): more undefined references to `myfree' follow ../common/libmammo.a(virtual_image.o): In function `allocate_cached_image': virtual_image.c:(.text+0x4233): undefined reference to `mycalloc' virtual_image.c:(.text+0x4253): undefined reference to `mymalloc' virtual_image.c:(.text+0x4275): undefined reference to `mycalloc' virtual_image.c:(.text+0x42e7): undefined reference to `mycalloc' virtual_image.c:(.text+0x44f9): undefined reference to `mycalloc' virtual_image.c:(.text+0x47a9): undefined reference to `mycalloc' virtual_image.c:(.text+0x4a45): undefined reference to `mycalloc' virtual_image.c:(.text+0x4af4): undefined reference to `myfree' collect2: error: ld returned 1 exit status make: *** [mkimage] Error 1 Building the breast segmentation program. gcc -O2 -I. -I../common breastsegment.o segment.o -o breastsegment -L../common -lmammo -lm breastsegment.o: In function `render_segmentation_sketch': breastsegment.c:(.text+0x43): undefined reference to `mycalloc' breastsegment.c:(.text+0x58): undefined reference to `mycalloc' breastsegment.c:(.text+0x12f): undefined reference to `mycalloc' breastsegment.c:(.text+0x1b9): undefined reference to `myfree' breastsegment.c:(.text+0x1c6): undefined reference to `myfree' breastsegment.c:(.text+0x1e1): undefined reference to `myfree' segment.o: In function `find_center': segment.c:(.text+0x53): undefined reference to `mycalloc' segment.c:(.text+0x71): undefined reference to `mycalloc' segment.c:(.text+0x387): undefined reference to `myfree' segment.o: In function `bordercode': segment.c:(.text+0x4ac): undefined reference to `mycalloc' segment.c:(.text+0x546): undefined reference to `mycalloc' segment.c:(.text+0x651): undefined reference to `mycalloc' segment.c:(.text+0x691): undefined reference to `myfree' segment.o: In function `estimate_tissue_image': segment.c:(.text+0x10d4): undefined reference to `mycalloc' segment.c:(.text+0x14da): undefined reference to `mycalloc' segment.c:(.text+0x1698): undefined reference to `mycalloc' segment.c:(.text+0x1834): undefined reference to `mycalloc' segment.c:(.text+0x1850): undefined reference to `mycalloc' segment.o:segment.c:(.text+0x186a): more undefined references to `mycalloc' follow segment.o: In function `estimate_tissue_image': segment.c:(.text+0x1bbc): undefined reference to `myfree' segment.c:(.text+0x1c4a): undefined reference to `mycalloc' segment.c:(.text+0x1c7c): undefined reference to `mycalloc' segment.c:(.text+0x1d8e): undefined reference to `myfree' segment.c:(.text+0x1d9b): undefined reference to `myfree' segment.c:(.text+0x1da8): undefined reference to `myfree' segment.c:(.text+0x1dba): undefined reference to `myfree' segment.c:(.text+0x1dc9): undefined reference to `myfree' segment.o:segment.c:(.text+0x1dd8): more undefined references to `myfree' follow segment.o: In function `estimate_tissue_image': segment.c:(.text+0x20bf): undefined reference to `mycalloc' segment.o: In function `segment_breast': segment.c:(.text+0x24cd): undefined reference to `mycalloc' segment.o: In function `find_center': segment.c:(.text+0x3a4): undefined reference to `myfree' segment.o: In function `bordercode': segment.c:(.text+0x6ac): undefined reference to `myfree' ../common/libmammo.a(aggregate.o): In function `aggregate': aggregate.c:(.text+0x7fa): undefined reference to `mycalloc' aggregate.c:(.text+0x81c): undefined reference to `mycalloc' aggregate.c:(.text+0x868): undefined reference to `mycalloc' ../common/libmammo.a(aggregate.o): In function `aggregate_median': aggregate.c:(.text+0xbc5): undefined reference to `mymalloc' aggregate.c:(.text+0xbfb): undefined reference to `mycalloc' aggregate.c:(.text+0xc3c): undefined reference to `mycalloc' ../common/libmammo.a(aggregate.o): In function `aggregate': aggregate.c:(.text+0x9b5): undefined reference to `myfree' ../common/libmammo.a(aggregate.o): In function `aggregate_median': aggregate.c:(.text+0xd85): undefined reference to `myfree' ../common/libmammo.a(cc_label.o): In function `cc_label': cc_label.c:(.text+0x20c): undefined reference to `mycalloc' cc_label.c:(.text+0x6c2): undefined reference to `mycalloc' cc_label.c:(.text+0xbaa): undefined reference to `myfree' ../common/libmammo.a(cc_label.o): In function `cc_label_0bkgd': cc_label.c:(.text+0xe17): undefined reference to `mycalloc' cc_label.c:(.text+0x12d7): undefined reference to `mycalloc' cc_label.c:(.text+0x17e7): undefined reference to `myfree' ../common/libmammo.a(cc_label.o): In function `cc_relabel_by_intensity': cc_label.c:(.text+0x18c5): undefined reference to `mycalloc' ../common/libmammo.a(cc_label.o): In function `cc_label_4connect': cc_label.c:(.text+0x1cf0): undefined reference to `mycalloc' cc_label.c:(.text+0x2195): undefined reference to `mycalloc' cc_label.c:(.text+0x26a4): undefined reference to `myfree' ../common/libmammo.a(cc_label.o): In function `cc_relabel_by_intensity': cc_label.c:(.text+0x1b06): undefined reference to `myfree' ../common/libmammo.a(convexpolyscan.o): In function `polyscan_coords': convexpolyscan.c:(.text+0x6f0): undefined reference to `mycalloc' convexpolyscan.c:(.text+0x75f): undefined reference to `mycalloc' convexpolyscan.c:(.text+0x7ab): undefined reference to `myfree' convexpolyscan.c:(.text+0x7b8): undefined reference to `myfree' ../common/libmammo.a(convexpolyscan.o): In function `polyscan_poly_cacheim': convexpolyscan.c:(.text+0x805): undefined reference to `mycalloc' convexpolyscan.c:(.text+0x894): undefined reference to `myfree' ../common/libmammo.a(mikesfileio.o): In function `read_segmentation_file': mikesfileio.c:(.text+0x1e9): undefined reference to `mycalloc' mikesfileio.c:(.text+0x205): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `linear_optical_density': optical_density.c:(.text+0x29e): undefined reference to `mymalloc' optical_density.c:(.text+0x342): undefined reference to `mycalloc' optical_density.c:(.text+0x383): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `log10_optical_density': optical_density.c:(.text+0x693): undefined reference to `mymalloc' optical_density.c:(.text+0x74f): undefined reference to `mycalloc' optical_density.c:(.text+0x790): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `map_with_ushort_lut': optical_density.c:(.text+0xb2e): undefined reference to `mymalloc' optical_density.c:(.text+0xb87): undefined reference to `mycalloc' optical_density.c:(.text+0xbc6): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `linear_optical_density': optical_density.c:(.text+0x4d9): undefined reference to `myfree' ../common/libmammo.a(optical_density.o): In function `log10_optical_density': optical_density.c:(.text+0x8f1): undefined reference to `myfree' ../common/libmammo.a(optical_density.o): In function `map_with_ushort_lut': optical_density.c:(.text+0xd0d): undefined reference to `myfree' ../common/libmammo.a(virtual_image.o): In function `deallocate_cached_image': virtual_image.c:(.text+0x3dc6): undefined reference to `myfree' virtual_image.c:(.text+0x3dd7): undefined reference to `myfree' ../common/libmammo.a(virtual_image.o):virtual_image.c:(.text+0x3de5): more undefined references to `myfree' follow ../common/libmammo.a(virtual_image.o): In function `allocate_cached_image': virtual_image.c:(.text+0x4233): undefined reference to `mycalloc' virtual_image.c:(.text+0x4253): undefined reference to `mymalloc' virtual_image.c:(.text+0x4275): undefined reference to `mycalloc' virtual_image.c:(.text+0x42e7): undefined reference to `mycalloc' virtual_image.c:(.text+0x44f9): undefined reference to `mycalloc' virtual_image.c:(.text+0x47a9): undefined reference to `mycalloc' virtual_image.c:(.text+0x4a45): undefined reference to `mycalloc' virtual_image.c:(.text+0x4af4): undefined reference to `myfree' collect2: error: ld returned 1 exit status make: *** [breastsegment] Error 1 Building the mass feature generation program. gcc -O2 -I. -I../common afumfeature.o -o afumfeature -L../common -lmammo -lm afumfeature.o: In function `afum_process': afumfeature.c:(.text+0xd80): undefined reference to `mycalloc' afumfeature.c:(.text+0xd9c): undefined reference to `mycalloc' afumfeature.c:(.text+0xe80): undefined reference to `mycalloc' afumfeature.c:(.text+0x11f8): undefined reference to `myfree' afumfeature.c:(.text+0x1207): undefined reference to `myfree' afumfeature.c:(.text+0x1214): undefined reference to `myfree' ../common/libmammo.a(aggregate.o): In function `aggregate': aggregate.c:(.text+0x7fa): undefined reference to `mycalloc' aggregate.c:(.text+0x81c): undefined reference to `mycalloc' aggregate.c:(.text+0x868): undefined reference to `mycalloc' ../common/libmammo.a(aggregate.o): In function `aggregate_median': aggregate.c:(.text+0xbc5): undefined reference to `mymalloc' aggregate.c:(.text+0xbfb): undefined reference to `mycalloc' aggregate.c:(.text+0xc3c): undefined reference to `mycalloc' ../common/libmammo.a(aggregate.o): In function `aggregate': aggregate.c:(.text+0x9b5): undefined reference to `myfree' ../common/libmammo.a(aggregate.o): In function `aggregate_median': aggregate.c:(.text+0xd85): undefined reference to `myfree' ../common/libmammo.a(convexpolyscan.o): In function `polyscan_coords': convexpolyscan.c:(.text+0x6f0): undefined reference to `mycalloc' convexpolyscan.c:(.text+0x75f): undefined reference to `mycalloc' convexpolyscan.c:(.text+0x7ab): undefined reference to `myfree' convexpolyscan.c:(.text+0x7b8): undefined reference to `myfree' ../common/libmammo.a(convexpolyscan.o): In function `polyscan_poly_cacheim': convexpolyscan.c:(.text+0x805): undefined reference to `mycalloc' convexpolyscan.c:(.text+0x894): undefined reference to `myfree' ../common/libmammo.a(mikesfileio.o): In function `read_segmentation_file': mikesfileio.c:(.text+0x1e9): undefined reference to `mycalloc' mikesfileio.c:(.text+0x205): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `linear_optical_density': optical_density.c:(.text+0x29e): undefined reference to `mymalloc' optical_density.c:(.text+0x342): undefined reference to `mycalloc' optical_density.c:(.text+0x383): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `log10_optical_density': optical_density.c:(.text+0x693): undefined reference to `mymalloc' optical_density.c:(.text+0x74f): undefined reference to `mycalloc' optical_density.c:(.text+0x790): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `map_with_ushort_lut': optical_density.c:(.text+0xb2e): undefined reference to `mymalloc' optical_density.c:(.text+0xb87): undefined reference to `mycalloc' optical_density.c:(.text+0xbc6): undefined reference to `mycalloc' ../common/libmammo.a(optical_density.o): In function `linear_optical_density': optical_density.c:(.text+0x4d9): undefined reference to `myfree' ../common/libmammo.a(optical_density.o): In function `log10_optical_density': optical_density.c:(.text+0x8f1): undefined reference to `myfree' ../common/libmammo.a(optical_density.o): In function `map_with_ushort_lut': optical_density.c:(.text+0xd0d): undefined reference to `myfree' ../common/libmammo.a(virtual_image.o): In function `deallocate_cached_image': virtual_image.c:(.text+0x3dc6): undefined reference to `myfree' virtual_image.c:(.text+0x3dd7): undefined reference to `myfree' ../common/libmammo.a(virtual_image.o):virtual_image.c:(.text+0x3de5): more undefined references to `myfree' follow ../common/libmammo.a(virtual_image.o): In function `allocate_cached_image': virtual_image.c:(.text+0x4233): undefined reference to `mycalloc' virtual_image.c:(.text+0x4253): undefined reference to `mymalloc' virtual_image.c:(.text+0x4275): undefined reference to `mycalloc' virtual_image.c:(.text+0x42e7): undefined reference to `mycalloc' virtual_image.c:(.text+0x44f9): undefined reference to `mycalloc' virtual_image.c:(.text+0x47a9): undefined reference to `mycalloc' virtual_image.c:(.text+0x4a45): undefined reference to `mycalloc' virtual_image.c:(.text+0x4af4): undefined reference to `myfree' collect2: error: ld returned 1 exit status make: *** [afumfeature] Error 1 Building the mass detection program. make: Nothing to be done for `all'. Building the performance evaluation program. gcc -O2 -I. -I../common DDSMeval.o polyscan.o -o DDSMeval -L../common -lmammo -lm ../common/libmammo.a(mikesfileio.o): In function `read_segmentation_file': mikesfileio.c:(.text+0x1e9): undefined reference to `mycalloc' mikesfileio.c:(.text+0x205): undefined reference to `mycalloc' collect2: error: ld returned 1 exit status make: *** [DDSMeval] Error 1 Building the template creation program. gcc -O2 -I. -I../common mktemplate.o polyscan.o -o mktemplate -L../common -lmammo -lm Building the drawimage program. gcc -O2 -I. -I../common drawimage.o -o drawimage -L../common -lmammo -lm ../common/libmammo.a(mikesfileio.o): In function `read_segmentation_file': mikesfileio.c:(.text+0x1e9): undefined reference to `mycalloc' mikesfileio.c:(.text+0x205): undefined reference to `mycalloc' collect2: error: ld returned 1 exit status make: *** [drawimage] Error 1 Building the compression/decompression program jpeg. gcc -O2 -DSYSV -DNOTRUNCATE -c lexer.c lexer.c:41:1: error: initializer element is not constant lexer.c:41:1: error: (near initialization for ‘yyin’) lexer.c:41:1: error: initializer element is not constant lexer.c:41:1: error: (near initialization for ‘yyout’) lexer.c: In function ‘initparser’: lexer.c:387:21: warning: incompatible implicit declaration of built-in function ‘strlen’ [enabled by default] lexer.c: In function ‘MakeLink’: lexer.c:443:16: warning: incompatible implicit declaration of built-in function ‘malloc’ [enabled by default] lexer.c:447:7: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:452:7: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:455:34: warning: incompatible implicit declaration of built-in function ‘calloc’ [enabled by default] lexer.c:458:7: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:460:3: warning: incompatible implicit declaration of built-in function ‘strcpy’ [enabled by default] lexer.c: In function ‘getstr’: lexer.c:548:26: warning: incompatible implicit declaration of built-in function ‘malloc’ [enabled by default] lexer.c:552:4: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:557:21: warning: incompatible implicit declaration of built-in function ‘calloc’ [enabled by default] lexer.c:557:28: warning: incompatible implicit declaration of built-in function ‘strlen’ [enabled by default] lexer.c:561:7: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c: In function ‘parser’: lexer.c:794:21: warning: incompatible implicit declaration of built-in function ‘calloc’ [enabled by default] lexer.c:798:8: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:1074:21: warning: incompatible implicit declaration of built-in function ‘calloc’ [enabled by default] lexer.c:1078:8: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:1116:21: warning: incompatible implicit declaration of built-in function ‘calloc’ [enabled by default] lexer.c:1120:8: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:1154:25: warning: incompatible implicit declaration of built-in function ‘calloc’ [enabled by default] lexer.c:1158:5: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:1190:5: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:1247:25: warning: incompatible implicit declaration of built-in function ‘calloc’ [enabled by default] lexer.c:1251:5: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c:1283:5: warning: incompatible implicit declaration of built-in function ‘exit’ [enabled by default] lexer.c: In function ‘yylook’: lexer.c:1867:9: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] lexer.c:1867:20: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] lexer.c:1877:12: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] lexer.c:1877:23: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] make: *** [lexer.o] Error 1

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  • Error on clicking on Text to Speech tab in Speech properties in Control Panel

    - by iceman
    When I click on Text to Speech tab in Speech properties I receive error: "C:\WINDOWS\system32\shell32.dll,Control_RunDLL "C:\Program Files\Common Files\Microsoft Shared\Speech\sapi.cpl",Speech". There's a hotfix mentioned the the KBs in MS support.For that MS sent me a password protected file ; 170483_ENU_i386_zip.exe which contained two files : WindowsXP-KB838659-x86-ENU.EXE and WINDOWSXP-KB838659-X86-ENU-Symbols.EXE . The first one did not install as it said i already had it and the second one unpacked some dlls which i don't know how to use. I also tried Re-registering sapi.dll on Windows XP using C:\Windows\System32\regsvr32.exe Is there any other fix to this error?

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  • What is the difference between System.Speech.Recognition and Microsoft.Speech.Recognition?

    - by Michael
    There are two similar namespaces and assemblies for speech recognition in .NET. I’m trying to understand the differences and when it is appropriate to use one or the other. There is System.Speech.Recognition from the assembly System.Speech (in System.Speech.dll). System.Speech.dll is a core DLL in the .NET Framework class library 3.0 and later There is also Microsoft.Speech.Recognition from the assembly Microsoft.Speech (in microsoft.speech.dll). Microsoft.Speech.dll is part of the UCMA 2.0 SDK I find the docs confusing and I have the following questions: System.Speech.Recognition says it is for "The Windows Desktop Speech Technology", does this mean it cannot be used on a server OS or cannot be used for high scale applications? The UCMA 2.0 Speech SDK ( http://msdn.microsoft.com/en-us/library/dd266409%28v=office.13%29.aspx ) says that it requires Microsoft Office Communications Server 2007 R2 as a prerequisite. However, I’ve been told at conferences and meetings that if I do not require OCS features like presence and workflow I can use the UCMA 2.0 Speech API without OCS. Is this true? If I’m building a simple recognition app for a server application (say I wanted to automatically transcribe voice mails) and I don’t need features of OCS, what are the differences between the two APIs?

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  • Is there a better approach to speech synthesis than text-to-speech for more natural output? [closed]

    - by Anne Nonimus
    We've all heard the output of text-to-speech systems, and for anything but very short phrases, it sounds very machine-like. The ultimate goal of speech synthesis systems is to pass a Turing test of hearing. Clearly, the state of the art in text-to-speech has much to improve. However, speech synthesis isn't restricted to just text-to-speech systems, and I'm wondering if other approaches have been tried with better success. In other words, has there been any work done (libraries, software, research papers, etc.) on natural speech synthesis other than text-to-speech systems?

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  • The Best Text to Speech (TTS) Software Programs and Online Tools

    - by Lori Kaufman
    Text to Speech (TTS) software allows you to have text read aloud to you. This is useful for struggling readers and for writers, when editing and revising their work. You can also convert eBooks to audiobooks so you can listen to them on long drives. We’ve posted some websites here where you can find some good TTS software programs and online tools that are free or at least have free versions available. 8 Deadly Commands You Should Never Run on Linux 14 Special Google Searches That Show Instant Answers How To Create a Customized Windows 7 Installation Disc With Integrated Updates

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  • Convert Audio File to text using System.Speech

    - by Kushal Kalambi
    I am looking to convert a .wav file recorded through an android phone at 16000 to text using C#; namely the System.Speech namespace. My code is mentioned below; recognizer.SetInputToWaveFile(Server.MapPath("~/spoken.wav")); recognizer.LoadGrammar(new DictationGrammar()); RecognitionResult result = recognizer.Recognize(); label1.Text = result.Text; The is working perfectly with sample .wav "Hello world" file. However when i record something on teh phone and try to convert to on the pc, the converted text is no where close to what i had recoreded. Is there some way to make sure the audio file is transcribed accurately?

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  • How to split a text file into multiple text files

    - by Andrew
    I have a text file called entry.txt that contains the following: [ entry1 ] 1239 1240 1242 1391 1392 1394 1486 1487 1489 1600 1601 1603 1657 1658 1660 2075 2076 2078 2322 2323 2325 2740 2741 2743 3082 3083 3085 3291 3292 3294 3481 3482 3484 3633 3634 3636 3690 3691 3693 3766 3767 3769 4526 4527 4529 4583 4584 4586 4773 4774 4776 5153 5154 5156 5628 5629 5631 [ entry2 ] 1239 1240 1242 1391 1392 1394 1486 1487 1489 1600 1601 1603 1657 1658 1660 2075 2076 2078 2322 2323 2325 2740 2741 2743 3082 3083 3085 3291 3292 3294 3481 3482 3484 3690 3691 3693 3766 3767 3769 4526 4527 4529 4583 4584 4586 4773 4774 4776 5153 5154 5156 5628 5629 5631 [ entry3 ] 1239 1240 1242 1391 1392 1394 1486 1487 1489 1600 1601 1603 1657 1658 1660 2075 2076 2078 2322 2323 2325 2740 2741 2743 3082 3083 3085 3291 3292 3294 3481 3482 3484 3690 3691 3693 3766 3767 3769 4241 4242 4244 4526 4527 4529 4583 4584 4586 4773 4774 4776 5153 5154 5156 5495 5496 5498 5628 5629 5631 I would like to split it into three text files: entry1.txt, entry2.txt, entry3.txt. Their contents are as follows. entry1.txt: [ entry1 ] 1239 1240 1242 1391 1392 1394 1486 1487 1489 1600 1601 1603 1657 1658 1660 2075 2076 2078 2322 2323 2325 2740 2741 2743 3082 3083 3085 3291 3292 3294 3481 3482 3484 3633 3634 3636 3690 3691 3693 3766 3767 3769 4526 4527 4529 4583 4584 4586 4773 4774 4776 5153 5154 5156 5628 5629 5631 entry2.txt: [ entry2 ] 1239 1240 1242 1391 1392 1394 1486 1487 1489 1600 1601 1603 1657 1658 1660 2075 2076 2078 2322 2323 2325 2740 2741 2743 3082 3083 3085 3291 3292 3294 3481 3482 3484 3690 3691 3693 3766 3767 3769 4526 4527 4529 4583 4584 4586 4773 4774 4776 5153 5154 5156 5628 5629 5631 entry3.txt: [ entry3 ] 1239 1240 1242 1391 1392 1394 1486 1487 1489 1600 1601 1603 1657 1658 1660 2075 2076 2078 2322 2323 2325 2740 2741 2743 3082 3083 3085 3291 3292 3294 3481 3482 3484 3690 3691 3693 3766 3767 3769 4241 4242 4244 4526 4527 4529 4583 4584 4586 4773 4774 4776 5153 5154 5156 5495 5496 5498 5628 5629 5631 In other words, the [ character indicates a new file should begin. Is there any way I can accomplish automatic text file splitting? My eventual, actual input entry.txt actually contains 200,001 entries. Doing the text split in either Windows or Linux would be great. I do not have access to a Mac machine. Thanks!

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  • Text inside <p> shrinks on mobile devices while div does not [migrated]

    - by guisasso
    I asked this question on stack overflow, but didn't get any answers, so I'm trying here. Does anybody know whats happening here? I tested on opera, dolphin and the factory android browser. (although it seems now to be working on opera) The div doesn't change size, but the text somehow is shrunk to fit on part of a div. Anyway to prevent this? Just to be clear, I'm trying to achieve on the mobile browser the same look as the pc version. As the problem seems to be with the browsers, how can I force the text to take the full width of the div? I tried setting the p tag to 100% with no success. The div has to have that width and be aligned to the left of the page. On a Pc, as it should be: I shrunk the code as much as I could: <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" lang="en-us"> <head> <meta content="text/html; charset=utf-8" http-equiv="Content-Type" /> <meta content="" name="keywords" /> <meta content="" name="description" /> <title></title> </head> <body> <div style="width:1000px; margin-left:auto; margin-right:auto;" > <div style="float:left; width:758px; background-color:aqua;"> <p> Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text .<br /> <br /> Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text Random text .<br /> <br /> Random text Random text Random text Random text <a href="http://www.a.com/a.html"> Random text </a> Random text Random text . </p> </div> </div> </body> </html> Thanks.

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  • C# Speech Recognition

    - by fonix232
    I am making a Smart House Control System right now, and I have a little problem. I was thinking on using Cosmos for a base system, and adding the needed namespace libraries to it, but as the usual System.Speech.Recognition namespace depends too much on Windows Speech API, I have to forget about using it. So my question is, is there any (free if possible) voice recognition and/or speech speech synthesizer library for C#, what has the following: support for multi-language speaking extracting text content from speech sample synthesizing speech with selectable (or user-written) speech pattern (voice) A general usage, non-windows dependent library would be the best, and of course, if it was free too.

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  • Speech recognition - MP3 to text software

    - by pako
    I'm looking for a speaker independent program (commercial or free) that would enable me to transcribe MP3 files containing speech recordings to text. I wanted to try Dragon Naturally Speaking, but it seems like it only supports transcribing my own speech recordings. So what are the alternatives?

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  • Sublime Text 2 'text bubbling'?

    - by Alex Mcp
    In vim and Notepad++ I have an awesome feature either mapped or built in that I've seen called text bubbling. I know about the Sublime documentation for mapping my own, but wanted to make sure I wasn't duplicating functionality: Basically when I have either block of text selected, or just a cursor on a line, I push (ctrl + up/down) or some other mapping, and the text is moved up or down, in a block, and the rest of the text 'flows' around it. Is this a native feature in Sublime Text or should I script it in?

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  • High quality (commercial) Text to English speech software? [closed]

    - by bodacydo
    I'm working on a software project and I am researching text-to-speech products to use. Does anyone know what are the current state of the art text-to-speech systems? Ideally the speech should be indistinguishable from a native American or English speaker. I'm looking for products with SDK or API that I can easily hook into. Just to clarify and iterate on my question - I'm not looking for things like Microsoft's free text-to-speech synthesis program, I'm looking for a high quality professional product.

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  • Looking for speech-to-text tool (convert .wav to text)

    - by David
    I have the ability to get .wav files of voice mails emailed to me, but sometimes I'll be sitting in a meeting and I need to know the content of a message without playing it out loud. Are there any good (and, preferably, free) tools for converting .wav files to text? I know Google Voice has this capability, but I can't determine if it'll work on a file-by-file basis. I realize that this is a difficult research problem, but even an 80% solution might be workable.

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  • System.Speech and Voices

    - by Attilah
    is it possible to create portable applications from Scansoft voices .exe files ? (www.portableapps.com). and then be able to access the voices programmatically through System.Speech namespace in .NET 3.5 ? I want to do that so I don't have to take a dedicated server just to install my text-to-speech web app. Help !

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  • How to dictate a Non-English text on an English Windows 7?

    - by hellelampe
    I'm using an English Windows 7 with speech recognition working fine if I'm dictating in English. I would like to dictate a letter in German. I don't need further features that let you use your computer without a mouse, I want to dictate my letter. If I just start speaking German the Windows speech recognition software just gives me English gibberish. When I set the Speech Recognition to "German" in the Speech Properties dialog, I get the error message: Speech Recognition could not start because the language configuration is not supported. The recognizer language must match the language of the user interface. Please change the recognizer language in the Speech Recognition control panel under Advanced Options. This error message doesn't help me, because it tells me that I either need to change my system language or the language I want to dictate. But that's not what I want. How can I dictate in German on my PC with the English version of Windows 7?

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  • EXCEL VBA STUDENTS DATABASE [on hold]

    - by BENTET
    I AM DEVELOPING AN EXCEL DATABASE TO RECORD STUDENTS DETAILS. THE HEADINGS OF THE TABLE ARE DATE,YEAR, PAYMENT SLIP NO.,STUDENT NUMBER,NAME,FEES,AMOUNT PAID, BALANCE AND PREVIOUS BALANCE. I HAVE BEEN ABLE TO PUT UP SOME CODE WHICH IS WORKING, BUT THERE ARE SOME SETBACKS THAT I WANT TO BE ADDRESSED.I ACTUALLY DEVELOPED A USERFORM FOR EACH PROGRAMME OF THE INSTITUTION AND ASSIGNED EACH TO A SPECIFIC SHEET BUT WHENEVER I ADD A RECORD, IT DOES NOT GO TO THE ASSIGNED SHEET BUT GOES TO THE ACTIVE SHEET.ALSO I WANT TO HIDE ALL SHEETS AND BE WORKING ONLY ON THE USERFORMS WHEN THE WORKBOOK IS OPENED.ONE PROBLEM AM ALSO FACING IS THE UPDATE CODE.WHENEVER I UPDATE A RECORD ON A SPECIFIC ROW, IT RATHER EDIT THE RECORD ON THE FIRST ROW NOT THE RECORD EDITED.THIS IS THE CODE I HAVE BUILT SO FAR.I AM VIRTUALLY A NOVICE IN PROGRAMMING. Private Sub cmdAdd_Click() Dim lastrow As Long lastrow = Sheets("Sheet4").Range("A" & Rows.Count).End(xlUp).Row Cells(lastrow + 1, "A").Value = txtDate.Text Cells(lastrow + 1, "B").Value = ComBox1.Text Cells(lastrow + 1, "C").Value = txtSlipNo.Text Cells(lastrow + 1, "D").Value = txtStudentNum.Text Cells(lastrow + 1, "E").Value = txtName.Text Cells(lastrow + 1, "F").Value = txtFees.Text Cells(lastrow + 1, "G").Value = txtAmountPaid.Text txtDate.Text = "" ComBox1.Text = "" txtSlipNo.Text = "" txtStudentNum.Text = "" txtName.Text = "" txtFees.Text = "" txtAmountPaid.Text = "" End Sub Private Sub cmdClear_Click() txtDate.Text = "" ComBox1.Text = "" txtSlipNo.Text = "" txtStudentNum.Text = "" txtName.Text = "" txtFees.Text = "" txtAmountPaid.Text = "" txtBalance.Text = "" End Sub Private Sub cmdClearD_Click() txtDate.Text = "" ComBox1.Text = "" txtSlipNo.Text = "" txtStudentNum.Text = "" txtName.Text = "" txtFees.Text = "" txtAmountPaid.Text = "" txtBalance.Text = "" End Sub Private Sub cmdClose_Click() Unload Me End Sub Private Sub cmdDelete_Click() 'declare the variables Dim findvalue As Range Dim cDelete As VbMsgBoxResult 'check for values If txtStudentNum.Value = "" Or txtName.Value = "" Or txtDate.Text = "" Or ComBox1.Text = "" Or txtSlipNo.Text = "" Or txtFees.Text = "" Or txtAmountPaid.Text = "" Or txtBalance.Text = "" Then MsgBox "There is not data to delete" Exit Sub End If 'give the user a chance to change their mind cDelete = MsgBox("Are you sure that you want to delete this student", vbYesNo + vbDefaultButton2, "Are you sure????") If cDelete = vbYes Then 'delete the row Set findvalue = Sheet4.Range("D:D").Find(What:=txtStudentNum, LookIn:=xlValues) findvalue.EntireRow.Delete End If 'clear the controls txtDate.Text = "" ComBox1.Text = "" txtSlipNo.Text = "" txtStudentNum.Text = "" txtName.Text = "" 'txtFees.Text = "" txtAmountPaid.Text = "" txtBalance.Text = "" End Sub Private Sub cmdSearch_Click() Dim lastrow As Long Dim currentrow As Long Dim studentnum As String lastrow = Sheets("Sheet4").Range("A" & Rows.Count).End(xlUp).Row studentnum = txtStudentNum.Text For currentrow = 2 To lastrow If Cells(currentrow, 4).Text = studentnum Then txtDate.Text = Cells(currentrow, 1) ComBox1.Text = Cells(currentrow, 2) txtSlipNo.Text = Cells(currentrow, 3) txtStudentNum.Text = Cells(currentrow, 4).Text txtName.Text = Cells(currentrow, 5) txtFees.Text = Cells(currentrow, 6) txtAmountPaid.Text = Cells(currentrow, 7) txtBalance.Text = Cells(currentrow, 8) End If Next currentrow txtStudentNum.SetFocus End Sub Private Sub cmdSearchName_Click() Dim lastrow As Long Dim currentrow As Long Dim studentname As String lastrow = Sheets("Sheet4").Range("A" & Rows.Count).End(xlUp).Row studentname = txtName.Text For currentrow = 2 To lastrow If Cells(currentrow, 5).Text = studentname Then txtDate.Text = Cells(currentrow, 1) ComBox1.Text = Cells(currentrow, 2) txtSlipNo.Text = Cells(currentrow, 3) txtStudentNum.Text = Cells(currentrow, 4) txtName.Text = Cells(currentrow, 5).Text txtFees.Text = Cells(currentrow, 6) txtAmountPaid.Text = Cells(currentrow, 7) txtBalance.Text = Cells(currentrow, 8) End If Next currentrow txtName.SetFocus End Sub Private Sub cmdUpdate_Click() Dim tdate As String Dim tlevel As String Dim tslipno As String Dim tstudentnum As String Dim tname As String Dim tfees As String Dim tamountpaid As String Dim currentrow As Long Dim lastrow As Long 'If Cells(currentrow, 5).Text = studentname Then 'txtDate.Text = Cells(currentrow, 1) lastrow = Sheets("Sheet4").Range("A" & Columns.Count).End(xlUp).Offset(0, 1).Column For currentrow = 2 To lastrow tdate = txtDate.Text Cells(currentrow, 1).Value = tdate txtDate.Text = Cells(currentrow, 1) tlevel = ComBox1.Text Cells(currentrow, 2).Value = tlevel ComBox1.Text = Cells(currentrow, 2) tslipno = txtSlipNo.Text Cells(currentrow, 3).Value = tslipno txtSlipNo = Cells(currentrow, 3) tstudentnum = txtStudentNum.Text Cells(currentrow, 4).Value = tstudentnum txtStudentNum.Text = Cells(currentrow, 4) tname = txtName.Text Cells(currentrow, 5).Value = tname txtName.Text = Cells(currentrow, 5) tfees = txtFees.Text Cells(currentrow, 6).Value = tfees txtFees.Text = Cells(currentrow, 6) tamountpaid = txtAmountPaid.Text Cells(currentrow, 7).Value = tamountpaid txtAmountPaid.Text = Cells(currentrow, 7) Next currentrow txtDate.SetFocus ComBox1.SetFocus txtSlipNo.SetFocus txtStudentNum.SetFocus txtName.SetFocus txtFees.SetFocus txtAmountPaid.SetFocus txtBalance.SetFocus End Sub PLEASE I WAS THINKING IF I CAN DEVELOP SOMETHING THAT WILL USE ONLY ONE USERFORM TO SEND DATA TO DIFFERENT SHEETS IN THE WORKBOOK.

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  • Server side speech to text

    - by teepusink
    Hi, I'm trying to install a speech recognition engine server side. (non commercial preferred since it's just for experimentation) The idea is to allow a user to say something from a website then whatever he/she says will show up on the screen (as text) I've read about many available softwares ranging from Microsoft Speech, Sphinx, Julius etc just not sure which one will perform best and easiest to install. Also do typically do I need to have root permission on my hosting to do this kind of stuff? I'm using a regular shared hosting right now. Thank you, Tee

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  • Quickest and easiest way to implement speech to text conversion for a small speech subset.

    - by sgtpeppers
    Hi, I want to implement a system that receives speech through a microphone on my Mac OS x. I know arbitrary speech recognition is close to impossible without training the system so I'm willing to restrict it to 10 simple sentences. It must recognize with a high degree of accuracy which of these 10 sentences are being spoken, generate the text and add an entry to a remote MySQL database. With these being the architecture of the system I want to implement, could anyone give me an overview of what would be the best way to go about implementing this system? I'm looking for ideas like open source libraries to minimize the coding as this is just a prototype application for a demonstration. Basically I'm looking for a quick and easy solution. Thanks!

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  • Speech.Recognition GrammarBuilder/Choices Tree Structure

    - by user2210179
    In playing around with C#'s Speech Recognition, I've stumbled across a road block in the creation of an effective GrammerBuilder with Choices (more specifically, Choices of Choices). IE considering the following logical commands. One solution would to "hard code" every combination of Speech lines and add them to a GrammarBuilder (ie "SET LEFT COLOR RED" and "SET RIGHT CLEAR", however, this would quickly max out the limit of 1024, especially when dealing with number combinations. Another solution would to Append all 'columns' as "Choices" (and filter out incorrect paths upon 'recognition', however this seems like it's processor heavy and unnecessary. The middle ground, seems like the best path - with Choices of Choices - like a tree structure on a GrammarBuilder - however I'm not sure how to proceed. Any suggestions?

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  • Using a "white list" for extracting terms for Text Mining

    - by [email protected]
    In Part 1 of my post on "Generating cluster names from a document clustering model" (part 1, part 2, part 3), I showed how to build a clustering model from text documents using Oracle Data Miner, which automates preparing data for text mining. In this process we specified a custom stoplist and lexer and relied on Oracle Text to identify important terms.  However, there is an alternative approach, the white list, which uses a thesaurus object with the Oracle Text CTXRULE index to allow you to specify the important terms. INTRODUCTIONA stoplist is used to exclude, i.e., black list, specific words in your documents from being indexed. For example, words like a, if, and, or, and but normally add no value when text mining. Other words can also be excluded if they do not help to differentiate documents, e.g., the word Oracle is ubiquitous in the Oracle product literature. One problem with stoplists is determining which words to specify. This usually requires inspecting the terms that are extracted, manually identifying which ones you don't want, and then re-indexing the documents to determine if you missed any. Since a corpus of documents could contain thousands of words, this could be a tedious exercise. Moreover, since every word is considered as an individual token, a term excluded in one context may be needed to help identify a term in another context. For example, in our Oracle product literature example, the words "Oracle Data Mining" taken individually are not particular helpful. The term "Oracle" may be found in nearly all documents, as with the term "Data." The term "Mining" is more unique, but could also refer to the Mining industry. If we exclude "Oracle" and "Data" by specifying them in the stoplist, we lose valuable information. But it we include them, they may introduce too much noise. Still, when you have a broad vocabulary or don't have a list of specific terms of interest, you rely on the text engine to identify important terms, often by computing the term frequency - inverse document frequency metric. (This is effectively a weight associated with each term indicating its relative importance in a document within a collection of documents. We'll revisit this later.) The results using this technique is often quite valuable. As noted above, an alternative to the subtractive nature of the stoplist is to specify a white list, or a list of terms--perhaps multi-word--that we want to extract and use for data mining. The obvious downside to this approach is the need to specify the set of terms of interest. However, this may not be as daunting a task as it seems. For example, in a given domain (Oracle product literature), there is often a recognized glossary, or a list of keywords and phrases (Oracle product names, industry names, product categories, etc.). Being able to identify multi-word terms, e.g., "Oracle Data Mining" or "Customer Relationship Management" as a single token can greatly increase the quality of the data mining results. The remainder of this post and subsequent posts will focus on how to produce a dataset that contains white list terms, suitable for mining. CREATING A WHITE LIST We'll leverage the thesaurus capability of Oracle Text. Using a thesaurus, we create a set of rules that are in effect our mapping from single and multi-word terms to the tokens used to represent those terms. For example, "Oracle Data Mining" becomes "ORACLEDATAMINING." First, we'll create and populate a mapping table called my_term_token_map. All text has been converted to upper case and values in the TERM column are intended to be mapped to the token in the TOKEN column. TERM                                TOKEN DATA MINING                         DATAMINING ORACLE DATA MINING                  ORACLEDATAMINING 11G                                 ORACLE11G JAVA                                JAVA CRM                                 CRM CUSTOMER RELATIONSHIP MANAGEMENT    CRM ... Next, we'll create a thesaurus object my_thesaurus and a rules table my_thesaurus_rules: CTX_THES.CREATE_THESAURUS('my_thesaurus', FALSE); CREATE TABLE my_thesaurus_rules (main_term     VARCHAR2(100),                                  query_string  VARCHAR2(400)); We next populate the thesaurus object and rules table using the term token map. A cursor is defined over my_term_token_map. As we iterate over  the rows, we insert a synonym relationship 'SYN' into the thesaurus. We also insert into the table my_thesaurus_rules the main term, and the corresponding query string, which specifies synonyms for the token in the thesaurus. DECLARE   cursor c2 is     select token, term     from my_term_token_map; BEGIN   for r_c2 in c2 loop     CTX_THES.CREATE_RELATION('my_thesaurus',r_c2.token,'SYN',r_c2.term);     EXECUTE IMMEDIATE 'insert into my_thesaurus_rules values                        (:1,''SYN(' || r_c2.token || ', my_thesaurus)'')'     using r_c2.token;   end loop; END; We are effectively inserting the token to return and the corresponding query that will look up synonyms in our thesaurus into the my_thesaurus_rules table, for example:     'ORACLEDATAMINING'        SYN ('ORACLEDATAMINING', my_thesaurus)At this point, we create a CTXRULE index on the my_thesaurus_rules table: create index my_thesaurus_rules_idx on        my_thesaurus_rules(query_string)        indextype is ctxsys.ctxrule; In my next post, this index will be used to extract the tokens that match each of the rules specified. We'll then compute the tf-idf weights for each of the terms and create a nested table suitable for mining.

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  • Coloring even heighten columns

    - by verror
    I try to set different a background colors for left and right columns and to maintain the same height. So I set a background color for outer wrapper ("container" div) so it will set a color to rightBar. But this didn't work. Online Demo I want it to work on all browsers. Markup: <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd"> <html lang="en"> <head> <title>Test</title> </head> <body> <div class="contentcontainer"> <div class="container"> <div class="mainBar"> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> <p>Text Text Text Text Text Text Text Text Text Text Text Text Text Text </p> </div> <div class="rightBar"> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> <p>BAR Text BAR Text BAR Text</p> </div> </div> </div> </body> </html> CSS: body { font-family: Verdana,Tahoma,Arial, "Trebuchet MS" ,Sans-Serif,Georgia,Courier, "Times New Roman" ,Serif; margin: 0px; padding: 0px; background: repeat-x scroll center bottom #C4DAE9; text-align:center; } .contentcontainer { } .container { margin-left: auto; margin-right: auto; margin-top:5px; width: 99%; text-align: left; background-color:Gray; clear:both; } .mainBar { width:70%; float:left; background-color:White; } .rightBar { width:30%; float:left; }

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  • Using a "white list" for extracting terms for Text Mining, Part 2

    - by [email protected]
    In my last post, we set the groundwork for extracting specific tokens from a white list using a CTXRULE index. In this post, we will populate a table with the extracted tokens and produce a case table suitable for clustering with Oracle Data Mining. Our corpus of documents will be stored in a database table that is defined as create table documents(id NUMBER, text VARCHAR2(4000)); However, any suitable Oracle Text-accepted data type can be used for the text. We then create a table to contain the extracted tokens. The id column contains the unique identifier (or case id) of the document. The token column contains the extracted token. Note that a given document many have many tokens, so there will be one row per token for a given document. create table extracted_tokens (id NUMBER, token VARCHAR2(4000)); The next step is to iterate over the documents and extract the matching tokens using the index and insert them into our token table. We use the MATCHES function for matching the query_string from my_thesaurus_rules with the text. DECLARE     cursor c2 is       select id, text       from documents; BEGIN     for r_c2 in c2 loop        insert into extracted_tokens          select r_c2.id id, main_term token          from my_thesaurus_rules          where matches(query_string,                        r_c2.text)>0;     end loop; END; Now that we have the tokens, we can compute the term frequency - inverse document frequency (TF-IDF) for each token of each document. create table extracted_tokens_tfidf as   with num_docs as (select count(distinct id) doc_cnt                     from extracted_tokens),        tf       as (select a.id, a.token,                            a.token_cnt/b.num_tokens token_freq                     from                        (select id, token, count(*) token_cnt                        from extracted_tokens                        group by id, token) a,                       (select id, count(*) num_tokens                        from extracted_tokens                        group by id) b                     where a.id=b.id),        doc_freq as (select token, count(*) overall_token_cnt                     from extracted_tokens                     group by token)   select tf.id, tf.token,          token_freq * ln(doc_cnt/df.overall_token_cnt) tf_idf   from num_docs,        tf,        doc_freq df   where df.token=tf.token; From the WITH clause, the num_docs query simply counts the number of documents in the corpus. The tf query computes the term (token) frequency by computing the number of times each token appears in a document and divides that by the number of tokens found in the document. The doc_req query counts the number of times the token appears overall in the corpus. In the SELECT clause, we compute the tf_idf. Next, we create the nested table required to produce one record per case, where a case corresponds to an individual document. Here, we COLLECT all the tokens for a given document into the nested column extracted_tokens_tfidf_1. CREATE TABLE extracted_tokens_tfidf_nt              NESTED TABLE extracted_tokens_tfidf_1                  STORE AS extracted_tokens_tfidf_tab AS              select id,                     cast(collect(DM_NESTED_NUMERICAL(token,tf_idf)) as DM_NESTED_NUMERICALS) extracted_tokens_tfidf_1              from extracted_tokens_tfidf              group by id;   To build the clustering model, we create a settings table and then insert the various settings. Most notable are the number of clusters (20), using cosine distance which is better for text, turning off auto data preparation since the values are ready for mining, the number of iterations (20) to get a better model, and the split criterion of size for clusters that are roughly balanced in number of cases assigned. CREATE TABLE km_settings (setting_name  VARCHAR2(30), setting_value VARCHAR2(30)); BEGIN  INSERT INTO km_settings (setting_name, setting_value) VALUES     VALUES (dbms_data_mining.clus_num_clusters, 20);  INSERT INTO km_settings (setting_name, setting_value)     VALUES (dbms_data_mining.kmns_distance, dbms_data_mining.kmns_cosine);   INSERT INTO km_settings (setting_name, setting_value) VALUES     VALUES (dbms_data_mining.prep_auto,dbms_data_mining.prep_auto_off);   INSERT INTO km_settings (setting_name, setting_value) VALUES     VALUES (dbms_data_mining.kmns_iterations,20);   INSERT INTO km_settings (setting_name, setting_value) VALUES     VALUES (dbms_data_mining.kmns_split_criterion,dbms_data_mining.kmns_size);   COMMIT; END; With this in place, we can now build the clustering model. BEGIN     DBMS_DATA_MINING.CREATE_MODEL(     model_name          => 'TEXT_CLUSTERING_MODEL',     mining_function     => dbms_data_mining.clustering,     data_table_name     => 'extracted_tokens_tfidf_nt',     case_id_column_name => 'id',     settings_table_name => 'km_settings'); END;To generate cluster names from this model, check out my earlier post on that topic.

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  • HTML: How to create a DIV with only vertical scroll-bar to show long paragraphs on a webpage?

    - by Awan
    I want to show terms and condition note on my website. I dont want to use text field and also dont want to use my whole page. I just want to display my text in selected area and want to use only vertical scroll-bar to go down and read all text. Currently I am using this code: <div style="width:10;height:10;overflow:scroll" > text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text text </div> It is not fixing the width and height and spread until the all text appears. Second it is showing horizontal scroll-bar and I don't want to show it. Any Idea ? Thanks

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