A Review of Feature Extraction Technique for Automatic Speech Recognition

Sandeep Joshi, Parag Parandkar

Abstract: Speech recognition is a multileveled pattern recognition task, in which acoustical signals are examined and structured into a hierarchy of subword units (e. g. , phonemes), words, phrases, and sentences. Each level may provide additional temporal constraints, e. g. , known word pronunciations or legal word sequences, which can compensate for errors or uncertainties at lower levels. This hierarchy of constraints can best be exploited by combining decisions probabilistically at all lower levels, and making discrete decisions only at the highest level. .

Keywords: ASR, Mel frequency, Cepstrum coefficient, feature & vector space, distance measurement

How to Cite?: Sandeep Joshi, Parag Parandkar, "A Review of Feature Extraction Technique for Automatic Speech Recognition", Volume 4 Issue 2, February 2015, International Journal of Science and Research (IJSR), Pages: 435-440, https://www.ijsr.net/getabstract.php?paperid=SUB151198, DOI: https://dx.doi.org/10.21275/SUB151198