Bessel features for detection of voice onset time using AM-FM signal

Voice onset time is an important temporal feature which is often overlooked in speech perception, speech recognition as well as accent detection. The VOT in unvoiced stops varies with a number of factors, among which the most established one is the place of articulation. In this paper we propose an approach for the automatic detection of VOT. The proposed method uses Bessel expansion to emphasize the vowel and consonant regions of stop consonant vowel units (SCV) such as /ka/, /Ta/, /ta/ and /pa/. AM-FM signal has been emphasized after appropriate consideration of the range of Bessel coefficients, separately for the vowel and consonant regions of SCV units. The reconstructed signal from the Bessel expansion is a narrow-band AM-FM signal, therefore the amplitude envelope (AE) function for the emphasized signal can be estimated using discrete energy separation algorithm (DESA). For the detection of VOT, both the AE of vowel and consonat emphasized signal has been analyzed. Detection of VOT is analyzed for the continuous speech corpus consisting of recording television broadcast news bulletins.