CMUSphinx and pocketSphinx

# CMUSphinx and pocketSphinx

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## CMUSphinx and pocketSphinx

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1. CMUSphinx andpocketSphinx

3. Running pocketsphnix • Note audio file in CMUSphinx\pocketsphinx\test\data\goforward.raw • Open terminal and • Change directory to d:\Stephans\CMUSphinx\pocketsphinx\bin\Release • Pocketsphinx_batch.exe should be there, unless compile failed • Make file ctlFile.txt with text of the name of the file we will decode • goforward • Make file called argFile.txt with contents (more about these later) • -hmm ../../model/hmm/en_US/hub4wsj_sc_8k • -lm ../../model/lm/en/turtle.DMP • -dict ../../model/lm/en/turtle.dic • Move • CMUSphinx/sphinxbase/bin/Release/sphinxbase.dll • To • CMUSphinx/pocketsphinx/bin/Release • Move • CMUSphinx\pocketsphinx\test\data\goforward.raw • To • CMUSphinx\pocketsphinx\bin\Release\goforward.raw • run • pocketsphinx_batch.exe -argfile argFile.txt -cepdir ../../test/data -ctl ctlFile.txt -cepext .raw -adcin true -hyp out.txt • Note: the command line arguments must be in this order!! • Where • -argfile argFile.txt defines the name of the arguments file. These aurgments are displayed on the screen when the program runs. You can check if they match • -cepdir ../../test/data defines the path to the files to be processed • -cepdir must come before -ctl • -ctl ctlFile.txt defines the ctlFile, which contains the name of the files to process. These names cannoy have the path or the extension • -cepext .raw defines the extension of the files in the ctlFile • -adcin true means that the files are audio files • -hyp out.txt defines the output file • More details on the parameters are http://manpages.ubuntu.com/manpages/lucid/man1/pocketsphinx_batch.1.html • After running, the outfile contains • go forward ten meters (goforward -26532)

4. Make and decode a new audio file • Open windows sound recorder • Record “go forward ten meters” • Save as myGoForward.wma • Saves as .wma file • Get wma to wav converted • Save as c:\pocketsphnix\test\data\myGoForward.wav • I use 4musics multiformat converted. Other converters should work • Change ctlFile.txt to • myGoForward • In terminal run • pocketsphinx_batch.exe -argfile argFile.txt -ctl ctlFile.txt -cepdir./ -cepext.wav -adcin true -hypout2.txt • Check that out2.txt says go forward ten meters

5. Make your own acoustic model and language • We will go over the what is going on later. But first, let’s try the process. • Alternatively, you can read the about what is going on first and then return to this section • Download data • http://www.speech.cs.cmu.edu/databases/an4/index.html • Get mswav version • Save it to your CMUSphinx directory • Decompress

6. models • Three types of models are used • acoustic model • Used to model the sound of a phone • Typically, this a HMM is used • Each phone has a HMM • Mapping from HMMs to phones • Since the acoustic model is a HMM, in the CMU Sphinx the HMM is the same as the acoustic model • phonetic dictionary • Maps phones to words • In CMU Sphinx, .dic files are dictionary files • language model • Used to determine sequences of words are allowed. For example, “he super run the sally” is not allowed in the language model

7. Set up config file • From CMUSphinx\SphinxTrain\etc • Copy • feat.params • sphinx_train.cfg • To CMUSphinx\an4\etc • Sphinc_train.cfg is the main configuration file • Open sphinx_train.cfg in an editor • Line 6: $CFG_DB_NAME = “an4”; • Line 7:$CFG_BASE_DIR = "d:\\stephans\\CMUSphinx\\an4"; • Line 8: $CFG_SPHINXTRAIN_DIR = "d:\\Stephans\\CMUSphinx\\SphinxTrain"; • Line 11:$CFG_BIN_DIR = "d:\\Stephans\\CMUSphinx\\sphinxbase\\bin\\Release"; • Line 13: $CFG_SCRIPT_DIR = "d:\\Stephans\\CMUSphinx\\SphinxTrain\\scripts"; • Check out line 19-21. These say where the wav files are and that we are using mswav, which is what we downloaded • Line 232:$DEC_CFG_DB_NAME = 'an4'; • Line 233: $DEC_CFG_BASE_DIR = 'd:\\Stephans\\CMUSphinx\\an4'; • Line 234 does not seem to matter • Line 239:$DEC_CFG_BIN_DIR = "d:\\Stephans\\CMUSphinx\\pocketsphinx\\bin\\Release"; • Save sphinx_train.cfg

8. Other changes • copy sphinxbase.dll from • CMUSphinx\sphinxbase\bin\Release • To • CMUSphinx\SphinxTrain\bin\Release • In CMUSphinx\an4\etc directory, copy or rename • an4.ug.lm.DMP to an4.lm.DMP • Open CMUSphinx\SphinxTrain\scripts\sphinxtrain.in in an editor • Line 3: sphinxpath="d:\\Stephans\\CMUSphinx“ • In many places is /lib/sphinxtrain. Change this to /SphinxTrain • Copy files • From CMUSphinx\pocketsphinx\bin\Release, copy • pocketspinx_batch.exe and pocketsphinx.dll to CMUSphinx\SphinxTrain/bin/Release • Try skipping this and setting line 243 of .cfg

9. check • Open a cmd prompt • Type path and make sure that the directory to • python is there • SphinxTrain\bin\Release is there

10. Run training • Change to CMUSphinx\an4 directory • Run • python ..\SphinxTrain\scripts\sphinxtrain.in run • This will take a while (15 minutes) • Results from test is sentence error rate of 45% (nearly half of the sentences had at least one error) and 15.7% word error rate (15.7% of the words were incorrectly estimated) • This can fail because python was not installed or the path to python was not set • Or the path to SphinxTrain

11. Check log • Open an4.html • Check for errors • MODULE: 30 Training Context Dependent models • A few errors of type: “Failed to align audio to trancript: final state of the search is not reached” are acceptable • MODULE: 50 Training Context dependent models • A few errors of type: “Failed to align audio to trancript: final state of the search is not reached” are acceptable • At the very end is the test decoding • Open log file • Note parameters for running decoding, specifically, where Hmm, dic, and lm is

12. Test with your own voice sample • Record sample • Convert to .wav • Run pocketsphinx_batch • pocketsphinx_batch • -hmm d:\Stephans\CMUSphinx\an4/model_parameters/an4.cd_cont_200 • -lw 10 -feat 1s_c_d_dd • -beam 1e-80 -wbeam 1e-40 • -dict d:\Stephans\CMUSphinx\an4/etc/an4.dic • -lm d:\Stephans\CMUSphinx\an4/etc/an4.lm.DMP • -wip 0.2 -ctl d:\Stephans\CMUSphinx\an4/myTest/ctlFile.txt • -ctloffset 0 • -ctlcount 130 • -cepdir d:\Stephans\CMUSphinx\an4/myTest -cepext .wav • -hyp d:\Stephans\CMUSphinx\an4/myTest/results.txt • -agcnone • -varnorm no • -cmn current • -adcin true

13. test

14. background • At a first approximation, words are a sequences of sounds, where each sound is a phone. • However, the exactly pronunciation of a phone depends on the phones before and after. • Diphones are two phones. Diphones are less impacted by the phones that come before or after. • Triphones and quinphones are possible. The general name is senone • While there are many phones, not all combinations of a phone is a word. Thus, we should not simple recognize phones, by recognize words as a sequence of phones • Besides phones are fillers (e.g., breath, “um”). An Utterance is a sequence of words and fillers • Utterances are separated by a pause

15. models • Three types of models are used • acoustic model • Used to model the sound of a phone • Typically, this a HMM is used • Each phone has a HMM • Mapping from HMMs to phones • Since the acoustic model is a HMM, in the CMU Sphinx the HMM is the same as the acoustic model • phonetic dictionary • Maps phones to words • In CMU Sphinx, .dic files are dictionary files • language model • Used to determine sequences of words are allowed. For example, “he super run the sally” is not allowed in the language model

16. Running with other models • Many acoustic and language models are available at • http://sourceforge.net/projects/cmusphinx/files/Acoustic%20and%20Language%20Models/

17. Building Your Own Acoustic Model and Language Model • Building your own models is time consuming • Acoustic models require • Lots of recordings of people saying words and sentences • Not that difficult to do • Accurate transcription of the recording • Time consuming • There are many acoustic models available online • It is possible to take an existing model are quickly adapt it to a particular speaker • Language Model • Different systems need different language models • A voice control for your TV needs to recognize only a few words like “volume up,” “change channel,” … • A voice driven email composer needs to recognize a different set of words • The performance of the recognizer is improved if your language only considers the relevant words. • You can take an existing language model and trim it to what you need, or make on from scratch • Many models are available from http://www.ldc.upenn.edu/Catalog/index.jsp

18. example • To explore acoustic and language models, get the AN4 database • http://www.speech.cs.cmu.edu/databases/an4/index.html • Save it to your CMUSphinx directory • Decompress • Also, explore the PDA dataset • http://www.speech.cs.cmu.edu/databases/pda/index.html • This data is from letters and numbers, e.g., “A”, “B”, “19” • We can test this system by saying things like “A”, “B”, etc.

19. Acoustic model • The acoustic model is used to translate recorded sounds into labeled phones, • e.g., recorded sound in file asc.wav is “AH” • Roughly speaking, acoustic models take the sound sample as input and the quality of fit as output • asc.wav -> AH-Model-> -12 • asc.wav -> AY-Model-> -14 • … • AH-Model gives a better fit of the recorder sound • Making a acoustic model is called training • Inputs to training are audio files and transcriptions • Challenge: Usually the audio file has many phones, not just one • E.g., from AN4 data set, an audio file contains a recording of the words “TWO SIX EIGHT FOUR FOUR ONE EIGHT “ • CMUSphinx\an4\wav\an4_clstk\fash\cen7-fash-b.wav • E.g. from PDA data set, an audio file might contain a recording of the words: “MARGINS HISTORICALLY HAVE PEAKED BY MID YEAR HE SAYS” • CMUSphinx\PDA\PDAs\001\PDAs01_001_1.wav

20. Transcriptions • Approach one: the recording from the PDA set is transcribed as: M AA R JH AX N Z SIL HH IX S T AO R IX K AX L IY SIL ... • Two problems with approach one • If the word margins are in other files, we need to enter the pronounciation of the word twice • There are two ways that people pronounce historically • HH IX S T AO R IX K AX L IY • HH IX S T AO R IX K L IY (this one actually says historicly, which is incorrect) • Two stage transciptions (results in many files) • Transcription file: gives the words spoken • This file contains one line for each file used in training • The line contains the text of the words spoken and the filename (without extension such as .wav) • The AN4 dataset includes the file an4_train_transcription and it includes the line: <s> TWO SIX EIGHT FOUR FOUR ONE EIGHT </s> (cen7-fash-b) • The PDA dataset includes the file PDAs.train_all.sent and it includes the line: MARGINS HISTORICALLY HAVE PEAKED BY MID YEAR HE SAYS (PDAs01_041) • Hmm, this is missing the <s> and </s>, I think that the software requires <s> and </s>.. To use the pda data set, add <s> and </s> • Dictionary file • A mapping from words to phones (elementary spoken sounds) • Allows words to have multiple pronunciations • E.g., the AN4 dataset includes the file an4.dic and it includes the lines • ELEVEN IH L EH V AH N • ELEVEN(2) IY L EH V AH N • E IY • By combining the transcript file and dictionary file, the sounds in each recorded audio file can be determined • However, it is a bit tricky to determine which part of the audio file corresponds to which sound. • This is a major challenge facing training • Recall, the overall goal of training is to find models for each sound. But to make the training process easier for the users, we only provide recordings of words and sentences.

21. Training • Files needed • your_db_train.fileids - List of files used for training • E.g., AN4 includes an4_train.fileids • Format • path/filename (without extension!) • The path is from where the SphinxTrain program is executed • E.g., an4_train.fileids path is relative to where AN4 /etc directory. So SphinxTrain needs to be run from this directory • your_db_train.transcription - Transcription for training (described on previous slide) • your_db.dic - Phonetic dictionary (described on previous slide) • your_db.filler - List of fillers and what they map to • Fillers are things like silence, breathing, “um” etc. • Fillers should also be used in the transcript • E.g., <s> TWO +UM+ SIX EIGHT FOUR FOUR ONE EIGHT </s> • Fillers use the + sign before and after • During training, models for fillers will be computed • Decoding is more complicated • Fillers are allowed to be added, but there is some penalty • the fillers are ignored when computing the probability of a sequence of words • E.g., the language model might tell us that “go to bed” is common, and “go up bed” is uncommon. If the decoder detect “go um to bed” it translates it to “go to bed” • For some reason, fillers are not used in the an4 and PDA transcript files • <s>, </s>, SIL are silence are included • SMACK is listed in the PDA filler file, but not in the transcript • File format • </s> SIL • <s> SIL • <sil> SIL • ++INHALE++ +INHALE+ • your_db.phone - Phoneset file • a list of all labels of phones used (sounds), including fillers • E.g., an4.phone: AA, AE, AH, … • Every phone label used in the dictionary must be in the .phone file AND the filler labels

22. Must have sphinxtrain/bin/debug in path • Must copy sphinxbase.dll to sphinxtrain/bin/debug or set path to • Move pocketsphinix exe and dll • Edit sphinxtrain.in to remove /log and set prefix to path • Must use python 2.7 • Delete an4.html before running • This is a log file. Will not exist before the first run. But if you run and find errors, you can check it. But make sure to delete it before running so you can see the errors • Change an4.ug.lm.DMP to an4.lm.DMP

23. Language model • Language models define which combinations of words are allowed. • And, which combinations are more common or less common • Language model defines • How often a word appears • Words: Go, stop, hi, bye • How often combinations of word appear • Combinations with 2 words: Go forward; go back; … • Note that the length of these sequences can be 2, 3, .. • The language cannot specify all combinations of any length. So only combinations up to some length (e.g., 2 or 3) are specified • .ARPA files specify the language with a particular format • See http://msdn.microsoft.com/en-us/library/hh378460.aspx for some details • See next slide • There is an online language maker that takes sentences, counts the combinations of words and makes a ARPA file • If you make your own arpa file, • you must sort it before using • sphinx_lm_sort < unsorted.arpa > sorted.arpa • Then convert to lm • sphinx_lm_convert –I sorted.arpa –o sorted.lm.DMP • Note that sometimes files that end in .lm are in the arpa format • The DMP can be used to decode

24. ARPA format • <header - information ignored by applications> • \data\ • ngram 1=9 • ngram 2=11 • ngram 3=3 • \1-grams: • -0.8953 <unk>        -0.7373 • -0.7404 </s> -0.6515 • -0.7861 <s>   -0.1764 • -1.0414 When -0.4754 • -1.0414 will -0.1315 • -0.9622 the   0.0080 • -1.4393 Stock -0.3100 • -1.0414 Go    -0.3852 • -0.9622 Up    -0.1286 • \2-grams: • -0.3626 <s> When     -0.1736 • -1.2765 <s> the      0.0000 • -1.2765 <s> Up       0.0000 • -0.2359 When will    0.1011 • -1.0212 will </s>    0.0000 • -0.4191 will the     0.0000 • -1.1004 the </s>     0.0000 • -1.1004 the Go       0.0000 • -0.6232 Stock Go     0.0000 • -0.2359 Go Up        0.0587 • -0.4983 Up </s>      • \3-grams: • -0.4260 <s> When will      • -0.6601 When will the      • -0.6601 Go Up </s>   • \end\ • /data/ specifies how many entries • The numbers are log10 of probabilities • For the 3-gram entry • -1.2 go to bed -.1. • The first number, -0.2 is log10 of the probability that the last word (bed) occurs given the first two words have occurred • There might be other 3-grams like go to sleep, etc. • The second number is the probability that no words occur after this 3-gram • For the 2-gram entry • -.2 go to -10.1 • The first number is the log10 of the probability that to occurs after go • The second number is the probability that no words will come after go to • Not so likely • For the 1-gram • -1.041 go -0.27 • The first number is the probability that go occurs • Go can occur by itself • The second number is not the log10 of a probability, but is log10 of a weight (it could be log10 of a probability, but does not have to be)

25. Running pocketsphinx on android • I could only get this working on Linux. • Windows might be possible (I didn’t try MAC) • The instructions here http://cmusphinx.sourceforge.net/2011/05/building-pocketsphinx-on-android/ are almost correct • Follow instructions for getting and compiling sphinxbase and pocketsphinx • Get PocketSphinxDemo.tar.gz • Import that to eclipse • File->import->Existing Projects into workspace-(next)- • Select “Select archive file” • browse and select PocketSphinxDemo.tar.gz • In an editor, open eclipse/workspace/PocketSphinxDemo/jni/Anroid.mk • In the second to last line • Change • LOCAL_STATIC_LIBRARIES := sphinxutilsphinxfesphinxfeatsphinxlmpocketsphinx • To • LOCAL_STATIC_LIBRARIES := pocketsphinxsphinxlmsphinxfeatsphinxfesphinxutil • (back to instructions from web page) • Build, • Change directory to eclipse/workspace/PocketSphinxDemo/jni • Android/andtroid-ndk-r7b/ndk-build –B • Adjust properties->Builders as described on web page • I’m not sure how important this is. • Swig makes an interface between java and c++, but these files have already been down loaded. • ndk is run from the command line

26. On phone • (the directory should be /mnt/sdcard/Android/data/edu.cmu.pocketsphinx) • adb shell • mkdir /mnt/sdcard/Android/data/edu.cmu.pocketsphinx • cd /mnt/sdcard/Android/data/edu.cmu.pocketsphinx • Make directory struction as shown on web page • /mnt/sdcard/Android/data/edu.cmu.pocketsphinx/hmm • /mnt/sdcard/Android/data/edu.cmu.pocketsphinx /hmm/en_US • /mnt/sdcard/Android/data/edu.cmu.pocketsphinx /hmm/hub4wsj_sc_8k • Not sure if this is needed. • /mnt/sdcard/Android/data/edu.cmu.pocketsphinx /lm • /mnt/sdcard/Android/data/edu.cmu.pocketsphinx/lm/en_US • Cd to CMUSphinx/pocketsphinx/model/hmm/en_US/ • Android/android-sdk/platform-tools/adb push ./hub4wsj_sc_8k /mnt/sdcard/Android/data/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k • Cd to CMUSphinx/pocketsphinx/model/lm • Android/android-sdk/platform-tools/adb push ./en_US /mnt/sdcard/Android/data/edu.cmu.pocketsphinx/lm/en_US/

27. In eclipse • In RecognizerTask.java, change code to include the correct path • This path must match the path where the model files are located • pocketsphinx.setLogfile("/mnt/sdcard/Android/data/edu.cmu.pocketsphinx/pocketsphinx.log");Config c = new Config();/** In 2.2 and above we can use getExternalFilesDir() or whatever it's called*/c.setString("-hmm", "/mnt/sdcard/Android/data/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k");c.setString("-dict", "/mnt/sdcard/Android/data/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.dic");c.setString("-lm", "/mnt/sdcard/Android/data/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.DMP");c.setString("-rawlogdir", "/mnt/sdcard/Android/data/edu.cmu.pocketsphinx"); // Only use it to store the audio • Note that these lines are also changed if you use different models • Build, run and test

28. Windows install • Requires Android NDK • Flex for windows: http://gnuwin32.sourceforge.net/packages/flex.htm • Bison for windows: http://gnuwin32.sourceforge.net/packages/bison.htm • Get CMUSphinix from here: ?? • Note that this contains the

29. Follow directions from • http://cmusphinx.sourceforge.net/2011/05/building-pocketsphinx-on-android/ • Or google: pocketSphinx android • Or: • But order of libs at the end need to be reversed • Only compiles on linux, because is need yacc

30. resources: • http://www.speech.cs.cmu.edu/sphinxman/

31. Voice activity detection • VAD is used to detect if anyone is speaking