Learning to Recognize Talkers From Natural, Sinewave, and Reversed Speech Samples

Sheffert, Sonya M.
Pisoni, David B.
Fellowes, Jennifer M.
Remez, Robert E.

¹Psychology Department, Central Michigan University
²Department of Psychology, Indiana University Bloomington
³Department of Psychiatry, Columbia University
⁴Department of Psychology, Barnard College.

⁵Correspondence concerning this article should be addressed to Sonya M. Sheffert, Psychology Department, Central Michigan University, Sloan Hall 214, Mount Pleasant, Michigan 48859. E-mail: [email protected].

Editor's Note. Carol Fowler served as the action editor for this article.—DAR

A portion of these findings was presented at the 134th Annual Meeting of the Acoustical Society of America, December 1997, San Diego, California. This research was supported by National Institute on Deafness and Other Communicative Disorders Grant DC00111 to Indiana University Bloomington and Grant DC00308 to Barnard College.

We thank Luis Hernandez for technical support, Nathan Large for assisting with data collection for Experiments 3–5, and Dalia Shoretz and Rebecca Piorkowski for lending scholarly and technical assistance to the project. We give special thanks to Vivian Tartter and two anonymous reviewers for their valuable comments on earlier versions of this article.

Received Date: October 4, 1999; Revised Date: April 24, 2002; Accepted Date: April 30, 2002

Journal of Experimental Psychology: Human Perception and Performance 28(6):p 1447-1469, December 2002.

In 5 experiments, the authors investigated how listeners learn to recognize unfamiliar talkers and how experience with specific utterances generalizes to novel instances. Listeners were trained over several days to identify 10 talkers from natural, sinewave, or reversed speech sentences. The sinewave signals preserved phonetic and some suprasegmental properties while eliminating natural vocal quality. In contrast, the reversed speech signals preserved vocal quality while distorting temporally based phonetic properties. The training results indicate that listeners learned to identify talkers even from acoustic signals lacking natural vocal quality. Generalization performance varied across the different signals and depended on the salience of phonetic information. The results suggest similarities in the phonetic attributes underlying talker recognition and phonetic perception.