2012-04-02 18:13:44 +04:00
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About TIMIT:
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2012-04-02 15:20:47 +04:00
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2012-04-02 18:13:44 +04:00
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Available as LDC corpus LDC93S1, TIMIT is one of the original
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clean speech databases. Description of catalog from LDC
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(http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC93S1):
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"The TIMIT corpus of read speech is designed to provide speech data
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for acoustic-phonetic studies and for the development and evaluation
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of automatic speech recognition systems. TIMIT contains broadband
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recordings of 630 speakers of eight major dialects of American English,
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each reading ten phonetically rich sentences. The TIMIT corpus includes
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time-aligned orthographic, phonetic and word transcriptions as well as
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a 16-bit, 16kHz speech waveform file for each utterance."
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2014-11-10 21:38:16 +03:00
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Note: please do not use this TIMIT setup as a generic example of how to run
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Kaldi, as TIMIT has a very nonstandard structure. Any of the other setups
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would be better for this purpose: e.g. librispeech/s5 is quite nice, and is
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free; yesno is very tiny and fast to run and is also free; and wsj/s5 has an
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unusually complete set of example scripts which may however be confusing.
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2012-04-02 18:13:44 +04:00
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Each subdirectory of this directory contains the scripts for a sequence
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of experiments.
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2015-09-01 04:13:22 +03:00
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s5: Monophone, Triphone GMM/HMM systems trained with Maximum Likelihood,
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followed by SGMM and DNN recipe.
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Training is done on 48 phonemes (see- Lee and Hon: Speaker-Independent
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2012-04-02 18:13:44 +04:00
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Phone Recognition Using Hidden Markov Models. IEEE TRANSACTIONS ON
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ACOUSTICS. SPEECH, AND SIGNAL PROCESSING, VOL. 31. NO. 11, PG. 1641-48,
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NOVEMBER 1989, ). In scoring we map to 39 phonememes, as is usually
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done in conference papers.
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The earlier versions of TIMIT scripts were implemented by Navdeep Jaitly,
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Arnab Ghoshal. Current version was developed by Bagher BabaAli and is
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maintained by Karel Vesely (vesis84@gmail.com).
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2012-04-02 15:20:47 +04:00
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