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.
