TIMIT Acoustic-Phonetic Continuous Speech Corpus

Item Name: TIMIT Acoustic-Phonetic Continuous Speech Corpus
Author(s): John S. Garofolo, Lori F. Lamel, William M. Fisher, Jonathan G. Fiscus, David S. Pallett, Nancy L. Dahlgren, Victor Zue
LDC Catalog No.: LDC93S1
ISBN: 1-58563-019-5
ISLRN: 664-033-662-630-6
DOI: https://doi.org/10.35111/17gk-bn40
Member Year(s): 1993
DCMI Type(s): Sound
Sample Type: 1-channel pcm
Sample Rate: 16000
Data Source(s): microphone speech
Application(s): speech recognition
Language(s): English
Language ID(s): eng
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC93S1 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Garofolo, John S., et al. TIMIT Acoustic-Phonetic Continuous Speech Corpus LDC93S1. Web Download. Philadelphia: Linguistic Data Consortium, 1993.
Related Works: View


TIMIT Acoustic-Phonetic Continuous Speech Corpus was a joint effort among the Massachusetts Institute of Technology (MIT), SRI International (SRI) and Texas Instruments, Inc. (TI). The speech was recorded at TI, transcribed at MIT and verified and prepared for CD-ROM production by the National Institute of Standards and Technology (NIST). It is comprised of approximately five hours of English speech along with time-aligned transcriptions. The TIMIT corpus of read speech is designed to provide speech data for acoustic-phonetic studies and for the development and evaluation of automatic speech recognition systems. TIMIT contains broadband recordings of 630 speakers of eight major dialects of American English, each reading ten phonetically rich sentences.


The TIMIT corpus includes time-aligned orthographic, phonetic and word transcriptions as well as a single channel, 16-bit, 16kHz speech waveform file for each utterance. The TIMIT corpus transcriptions have been hand verified. Test and training subsets, balanced for phonetic and dialectal coverage, are specified. Tabular computer-searchable information is included as well as written documentation. Speaker metadata includes gender, dialect, birth date, height, race, and education level. Of the 630 speakers, about 70% are men and 30% are women.



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