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Introduction to Speech Corpora@Stanford

Introduction to Speech Corpora@Stanford. Neal Snider, snider@stanford.edu For LIN110, April 12 th , 2005 (adapted from slides by Florian Jaeger). Before we get to the real stuff…. This presentation will be available online at:

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Introduction to Speech Corpora@Stanford

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  1. Introduction to Speech Corpora@Stanford Neal Snider, snider@stanford.edu For LIN110, April 12th, 2005 (adapted from slides by Florian Jaeger)

  2. Before we get to the real stuff… • This presentation will be available online at: • http://www.stanford.edu/dept/linguistics/corpora/material/ling110/ • Local support • Where are our corpora? • Setting up your account on AFS

  3. Local support • Where can you get help with your project? • Your TA • The Corpora@Stanford website (http://www.stanford.edu/dept/linguistics/corpora/) • The corpora@csli.stanford.edu email list (you have to subscribe first) • The corpus TA (snider@stanford.edu)

  4. Where are our corpora? (1) • AFS: • AFS is Stanford’s file sharing system • The linguistic corpora are stored at: /afs/ir/data/linguistic-data/ • You need to register for AFS access • You need to set up your account

  5. Where are our corpora? (2) • Corpus Computer • The computer is the one closest to the printer in the linguistics department’s computer cluster (MJH, 1st floor) • The corpora are stored on partition D:\ • Mapping the drive via a network:

  6. The real part • Example project • Overview of available corpora • Where to find them • How does the annotation look like? • How to search speech corpora

  7. Example projects (1) • Differences in the realization of phonemes depending on their context • ‘Context’ can be segmental [1] • How does the realization of syllabic /m/ differ depending on the preceding onset? • Word final vowel aspiration • ‘Context’ can be supra-segmental: [3] • How does the realization of syllabic /m/ differ at the beginning/end of conversations/utterances/sentences? • Reduction of complex clusters

  8. Example projects (2) • ‘Context’ could also include the register, style (formal vs. informal), genre (reading a fairy tale vs. reading an article), different dialects, etc. [2] • Pitch contours related to specific meanings [1] • Steady-state pitch contours

  9. Available corpora • Handout in http://www.stanford.edu/dept/linguistics/corpora/material/X_speech_corpora/X_phonetic corpora.doc • See also: • http://www.stanford.edu/dept/linguistics/corpora/

  10. Switchboard – spontaneous AE speech • Transcripts uploaded to AFS: • /afs/ir/data/linguistic-data/Switchboard/ • Sound files available on CD • available in several formats: • All in one file • Separate files for • Syllables • Words • Orthographic transcription

  11. Example annotations (Switchboard) • Some files in Switchboard

  12. Switchboard – all in one fileAnnotation key (1) Key: • SENTENCE: word1 word2 ... (2005_A_0041) • WORD: word canonical? [lm-probs] [rates] [positions] [morebigrams] part-of-speech phone1 phone2 ... • SYL: baseform transcribed syl_structure stress length [lm-probs] [rates] [positions] • PHONE: baseform stress syl_part [lm-probs] [rates] [positions] tran1 tran2 ...

  13. Switchboard – all in one fileAnnotation key (2) • [lm-probs]= trigram unigram trigram-unigram • [rates]= seg_tr_syl seg_tr_phn lex_syl lex_phn enrate vrate nvrate mrate mfrate enmmfrate mmfrate • [positions] = word_num_in_utterance word_num_in_turn • [morebigrams] = bigram reverse-bigram reverse-trigram center-trigram • part-of-speech = syntactic part of speech (currently only done for the word "to") • wordX= word number X in acoustically segmented `sentence' • canonical?= can if canonical (pronlex) pronunciation, alt otherwise • trigram= p(word | previous two words) • unigram= p(word) • trigram-unigram = difference between two probabilities • seg_tr_syl= transcribed syllable rate between closest two pauses • seg_tr_phn= transcribed phone rate between closest two pauses • lex_syl= lexical syllabic rate (i.e. as determined from wd transcription) • lex_phn= lexical phone rate (i.e. as determined from wd transcription)

  14. Switchboard – all in one fileAnnotation key (3) • enrate= old enrate measure • vrate= voicing rate • nvrate= another voicing rate • mrate= sub-part of mrate measure • mfrate= sub-part of mrate measure • enmmfrate= *this is what we call mrate* average of enrate, mrate, mfrate • mmffrate= average of mrate, mfrate • baseform= pronunciation as written in dictionary • transcribed= transcribed syllable • syl_structure= onset/nucleus/coda markings from dictionary • stress= syllable stress marking from dictionary P=primary S=secondary N=none • length= syllable length • tranX= transcribed phone X corresponding to baseform phone

  15. Arpabet

  16. Example annotations (Switchboard – all in one file) SENTENCE: like finding a proper nursing home (2005_A_0041) WORD: like 1 can -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 l ay k SYL: l_ay_k l_ay_k O_N_C P 0.258 -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 PHONE: l P O -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 l PHONE: ay P N -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 ay PHONE: k P C -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 k WORD: finding 2 alt -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 f ay n ih ng SYL: f_ay_n f_ay_n O_N_C P 0.358 -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 PHONE: f P O -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 f PHONE: ay P N -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 ay PHONE: n P C -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 n SYL: d_ih_ng NULL_ih_ng O_N_C N 0.117 -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 PHONE: d N O -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 NULL 1 27 PHONE: ih N N -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 ih PHONE: ng N C -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 ng

  17. Boston Radio Transcripts • Includes read news etc. (i.e. non-spontaneous read speech) • Transcripts uploaded to AFS at: • /afs/ir/data/linguistic-data/Boston-University-Radio • Sound files available on CD

  18. Example annotations (Boston Radio) • Boston News Corpus • H# 0 4 • >endsil • DH 4 5 • IH+1 9 10 • S 19 9 • >This • HH 28 5 • AA+1 33 9 • L 42 12 • AX 54 4 • DCL 58 3 • D 61 1 • EY 62 16 • >holiday • S 78 11 • IY+1 89 14 • Z 103 7 • EN 110 20 • …

  19. Example annotations (Boston Radio) • XWAVES/PRAAT readable: • signal st43/f3ast43p1 • type 1 • color 76 • font -*-times-medium-r-*-*-17-*-*-*-*-*-*-* • separator ; • nfields 1 • # • 0.035000 76 H# • 0.085000 76 DH • 0.185000 76 IH+1 • 0.275000 76 S • 0.325000 76 HH • 0.415000 76 AA+1 • 0.535000 76 L • 0.575000 76 AX • 0.605000 76 DCL • 0.615000 76 D • 0.775000 76 EY • 0.885000 76 S • …

  20. CALLHOME Mandarin - Transcripts • CALLHOME – Mandarin • Transcripts uploaded to AFS: • /afs/ir/data/linguistic-data/CALLHOME/CALLHOME-Mandarin-Transcripts/ • Lexicon with pronunciation information available at: • /afs/ir/data/linguistic-data/CALLHOME/CALLHOME-Mandarin-Lexicon/ • Sound files only available on CD/DVD, but I could put them on the corpus computer

  21. TIMIT – dialect variation • Telephone recording of 8 major dialects of American English • (orthographic) transcripts on AFS, sound files available on CD • Comparable dialect corpora exist for the British Isles (IViE; stored on the corpus computer)

  22. Example annotations (TIMIT) • TIMIT • Word label (.wrd): • 7470 11362 she • 11362 16000 had • 15420 17503 your • 17503 23360 dark • 23360 28360 suit • 28360 30960 in • 30960 36971 greasy • Phonetic label (.phn): • (Note: beginning and ending silence regions are marked with h#) • 0 7470 h# • 7470 9840 sh • 9840 11362 iy • 11362 12908 hv • 12908 14760 ae • 14760 15420 dcl • 15420 16000 jh • 16000 17503 axr

  23. How to search transcribed corpora? • Either load the files into your favorite text editor • Or use a command from the ‘grep’ family (run on a UNIX shell) • This allows you to search many files as once for patterns that are described by regular expressions • For help, see our tutorial page at: • http://www.stanford.edu/dept/linguistics/corpora/cas-tut-grep.html

  24. Example annotations (Switchboard – all in one file) SENTENCE: like finding a proper nursing home (2005_A_0041) WORD: like 1 can -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 l ay k SYL: l_ay_k l_ay_k O_N_C P 0.258 -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 PHONE: l P O -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 l PHONE: ay P N -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 ay PHONE: k P C -2.408 -2.152 -0.256 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 0 26 k WORD: finding 2 alt -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 f ay n ih ng SYL: f_ay_n f_ay_n O_N_C P 0.358 -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 PHONE: f P O -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 f PHONE: ay P N -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 ay PHONE: n P C -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 n SYL: d_ih_ng NULL_ih_ng O_N_C N 0.117 -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 PHONE: d N O -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 NULL 1 27 PHONE: ih N N -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 ih PHONE: ng N C -3.604 -4.256 0.652 4.64 10.43 3.87 9.89 3.80 2.32 5.79 2.32 4.64 3.59 3.48 1 27 ng

  25. Demo search egrep '^SYL: [a-z_]+ [a-z_]*ow.{1,3}m[a-z_]* ’ Actual phonological pattern

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