BREF, a large vocabulary spoken corpus for French
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This paper presents some of the design considerations of BREF, a large read-speech corpus for French. BREF was designed to provide continuous speech data for the development of dictation machines, for the evaluation of continuous speech recognition systems (both speaker-dependent and speakerindependent), and for the study of phonological variations. The texts to be read were selected from 5 million words of the French newspaper, Le Monde. In total, 11,000 texts were selected, with selection criteria that emphasisized maximizing the number of distinct triphones. Separate text materials were selected for training and test corpora. Ninety speakers have been recorded, each providing between 5,000 and 10,000 words (approximately 40-70 min.) of speech.
[1] Maxine Eskénazi,et al. Design considerations and text selection for BREF, a large French read-speech corpus , 1990, ICSLP.
[2] Patti Price,et al. The DARPA 1000-word resource management database for continuous speech recognition , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.
[3] George R. Doddington,et al. The ATIS Spoken Language Systems Pilot Corpus , 1990, HLT.