Speech recognition using recursive time-domain high-pass filtering of spectral feature vectors

摘要

A circuit arrangement for speech recognition carries out an analysis of a speech signal, extracting characteristic features. The extracted features are represented by spectral feature vectors which are compared with reference feature vectors stored for the speech signal to be recognized. The reference feature vectors are determined during a training phase in which a speech signal is recorded several times. A recognition result essentially depends on a quality of the spectral feature vectors and reference feature vectors. A recognition result essentially depends on a quality of the spectral feature vectors and reference feature vectors. A recursive high-pass filtering is performed in the time domain on the spectral feature vectors. Influences of noise signals on the recognition result are reduced by this and a high degree of speaker independence of the recognition is achieved. As a result, the circuit arrangement for speech recognition may also be used in systems requiring a speaker-independent speech recognition.