Detection of voice onset time using FB expansion and AM-FM model

The voice onset time (VOT) combines the temporal and frequency structure over very short duration. This makes the VOT detection task difficult. But the VOT is an important temporal feature. In this paper we propose a new method for the detection of VOT in speech utterances. The method uses Fourier-Bessel (FB) expansion followed by amplitude and frequency modulated (AM-FM) signal model. The FB expansion is used to emphasize the vowel and consonant regions of stop consonant vowel (SCV) units (/ka/, /ta/, and /pa/). The emphasized signals using selected range of FB coefficients have been considered narrow-band AM-FM signals. The discrete energy separation algorithm (DESA) has been used to estimate amplitude envelope (AE) function of the AM-FM model. The estimated AE function is explored for the detection of VOT. The VOT detection studies are carried out using the speech corpus consists of utterances of various male and female speakers.