Features for Automatic Detection of Voice Bars in Continuous Speech

In this paper we propose features for automatic detection of voice bar, which is an essential component of voiced stop consonants, in continuous speech. The acoustic-phonetic and production based knowledge such as, the presence of voicing, low strength of excitation compared to other voiced phones and a predominant low-frequency spectral energy, are mapped onto a set of acoustic features that can be automatically extracted from the signal. The usefulness of the proposed features in the detection of voice bars is studied using a knowledge-based as well as a neural network based approach. The performance of the proposed features and approaches is studied on phones from databases of two languages, namely English and Hindi.