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.
Bibliographic reference. Dhananjaya, N. / Rajendran, S. / Yegnanarayana, B. (2008): "Features for automatic detection of voice bars in continuous speech", In INTERSPEECH-2008, 1321-1324.