What Makes Your Voice Yours?

A large body of evidence from phonetics, cognitive psychology and neuropsychology indicates that listeners organize all this intra-talker variability into a prototype for each talker — an “average” representation — and a set of deviations from that prototype. Even a single syllable can carry enough information to distinguish one]“Voice quality is going to wander,” Keating said. “We are looking at the point when you stop sounding like yourself and start sounding like someone else.”

Keating and Kreiman digitally analyzed recordings from fifty women, all native speakers of English, who read five sentences twice on three different days. This analysis looked at multiple acoustic parameters for the vowel and consonant sounds making up the read sentences, such as fundamental frequency, intensities of harmonic frequencies relative to one another, and how they compare to the underlying noise levels within the voice.

These sentences provided each characteristic with a quantitative average and range, the collection of which formed a potential identifying voice profile of sorts. By comparing all of the speakers to this set of characteristics — a particular person’s voice profile — using a random set of their sample sentences, it could be tested for accuracy in distinguishing the correct speaker and compared to how well other sets of characteristics act to distinguish a particular voice.

This work expands on previous work the two have successfully completed with a sample of just three speakers. The larger sample size offers more insight to understanding which characteristics, and by what margin, make a recognizable voice unrecognizable. This is why the set of samples was comprised of similar speakers, all female and native English speakers.

“Who should be confusable and under what circumstances?” Kreiman asked. “How much of an acoustical change is perceptible?” Looking ahead, answering these questions may help in generating predictions about confusability in the context of both human listeners, who tend to be able to discern recognizably in a matter of seconds, and computer algorithms, that typically require samples closer to a minute in length.

Keating and Kreiman  presented preliminary findings of their research at the 172nd Meeting of the Acoustical Society of America and the 5th Joint Meeting with Acoustical Society of Japan, held Nov.28–Dec. 2, 2016, in Honolulu, Hawaii.