CSR-I (WSJ0) Complete
|Item Name:||CSR-I (WSJ0) Complete|
|Author(s):||John S. Garofolo, David Graff, Doug Paul, David Pallett|
|LDC Catalog No.:||LDC93S6A|
|Release Date:||May 30, 2007|
|Member Year(s):||1993, 1996|
|Sample Type:||1-channel pcm compressed|
|Data Source(s):||microphone speech|
LDC User Agreement for Non-Members
|Online Documentation:||LDC93S6A Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Garofolo, John S., et al. CSR-I (WSJ0) Complete LDC93S6A. Web Download. Philadelphia: Linguistic Data Consortium, 1993.|
LDC93S6A - Complete CSR-I corpus LDC93S6B - CSR-I Sennheiser speech LDC93S6C - CSR-I other speech
During 1991, the DARPA Spoken Language Program initiated efforts to build a new corpus to support research on large-vocabulary Continuous Speech Recognition (CSR) systems.
The first two CSR Corpora consist primarily of read speech with texts drawn from a machine-readable corpus of Wall Street Journal news text and are thus often known as WSJ0 and WSJ1. (Later sections of the CSR set of corpora, however, will consist of read texts from other sources of North American business news and eventually from other news domains).
The texts to be read were selected to fall within either a 5,000-word or a 20,000-word subset of the WSJ text corpus. (See the documentation for details). Some spontaneous dictation is included in addition to the read speech. The dictation portion was collected using journalists who dictated hypothetical news articles.
Two microphones are used throughout: a close-talking Sennheiser HMD414 and a secondary microphone, which may vary. The corpora are thus offered in three configurations: the speech from the Sennheiser, the speech from the other microphone and the speech from both; all three sets include all transcriptions, tests, documentation, etc.
In general, transcriptions of the speech, test data from ARPA evaluations, scores achieved by various speech recognition systems and software used in scoring are included on separate discs from the waveform data.
Please listen to this audio sample.