Robust automatic recognition of telephone speech

Abstract

A method is presented to compensate cepstral coefficients (MFCCs) in a speech recognition system for degraded telephone channel conditions. The technique proposed is based on a combination of the Karhonen–Loeve Transform (KLT) and Genetic Algorithms (GA). The idea consists of projecting the band-limited MFCCs onto a subspace generated by the genetically optimized KLT principal axes. Experiments show a clear improvement when the method was applied to the NTIMIT speech database. Word recognition results obtained on the HTK toolkit platform using N-mixture tri-phone models and a bigram language model are presented and discussed.