Abstract
Automatic speech recognition by computers can provide the most natural and efficient method of communication between humans and computers. While in recent years high performance speech recognition systems are beginning to emerge from research institutions, scientists unequivocally agree that the deployment of speech recognition systems into realistic operating environments will require many hours of speech data to help us model the inherent variability in the speech signal. This paper describes the experiences of researchers at MIT in the collection of two large speech databases which have somewhat complementary objectives. The timit database was designed to be task and speaker-independent, and is suitable for general acoustic-phonetic research. The voyager database, on the other hand, was intended for development and evaluation of a system which incorporates both speech and natural language processing. This database is particularly valuable as a source of spontaneous utterances elicited in a realistic goal-oriented environment.
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