Application of automatic speech recognition to evaluation of speech transmission quality in analog communication systems

Abstract

The preliminary results of application of automatic recognition of isolated words to objective evaluation of speech transmission quality in analog telephone channels are presented. A memoryless, finite state recognition system with LPC, FFT, and BF-FFT (where the speech signal was filtered in Bark bands) parametrization was applied. In classification stage a dynamic time warping and nearest-neighbor algorithm were utilized. Nonsense word lists consisting of 100 logotoms were recorded in a studio by a professional male speaker and utilized next as a test material. Speech transmission quality was examined in laboratory models of telephone channels with frequency bands of 300–3400, 400–2500, and 100–6000 Hz for speech-to-white-noise ratios in the range of +15 to −15 dB. The results of objective measurements expressed in percent of logotoms correctly recognized by the recognition system were compared under the same transmission conditions with subjectively measured logotom intelligibility. The best agreement between subjective and objective evaluation of speech transmission quality was obtained for automatic speech recognition utilizing BF–FFT parametrization. The results of objective evaluation of speech transmission quality by means of the presented method are encouraging and the experiments will be continued for other communication channels (e.g., digital) and different distortions and disturbances.