Speech perception research at UTD

Listeners can extract information from speech produced under extreme conditions: for example, when the speaking rate is 400 words per minute; in high levels of background noise; and when the identity of the speaker is unknown. Current research in our laboratory considers how human listeners achieve this by looking at auditory, perceptual, and cognitive processes that intervene between the production of speech and its recognition. We are developing and testing models of the auditory and phonetic analysis of speech to describe how listeners extract information from speech when competing sound sources are present. When the competing sound source is another voice, listeners face the difficult problem of separating signals that are similar in their acoustic structure. This problem has serious implications for theoretical models of speech perception, and it has important practical consequences for two areas of applied speech research. First, because competing voices present difficulties for individuals suffering from sensorineural hearing impairments, research on the perceptual processes involved in speech-source segregation may provide insights into the problems faced by these listeners, and may suggest forms of signal processing to enhance the intelligibility of speech signals corrupted by background noise. Second, because competing voices severely degrade the performance of automatic speech recognizers, it is likely that a better understanding of human performance will lead to improvements in the design of robust and noise-resistant devices for automatic speech recognition.

Current projects


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