Automatic detection of irregular phonation in continuous speech

Voice quality is one of the most important source characteristics of a speaker’s speech production process, and creakiness is one of the variations of voice quality. This paper describes the development of an algorithm to automatically detect irregular phonation, including creakiness and other variations, in continuous running speech. The algorithm is an extension of the Aperiodicity, Periodicity and Pitch (APP) Detector. The algorithm has been run on 485 files of the TIMIT database, which contained 677 instances of irregular phonation. The test set comprised of 97 speakers, of which 57 were male and 40 were female. The algorithm has been found to give an accuracy of 86.7 % on average, with performance being almost the same for both male and female speakers. Automatic detection of irregular phonation should help characterize speakers for speaker identification applications.