Output-based objective speech quality

Objective speech quality measures automatically assess performance of communication systems without the need for human listeners. Typical objective quality methods are based on some distortion measure between the known input speech record and the received output signal. This paper describes experiments to develop a new technique that requires only the received speech. The algorithm uses perceptually-based speaker-independent speech parameters such as perceptual-linear prediction coefficients and the perceptually weighted Bark spectrum. Parameters derived from a variety of undegraded source speech material provides reference centroids corresponding to high speech quality. The average distance between output speech parameters and the nearest reference centroid provides an indication of speech degradation, which is used to estimate subjective quality. The paper presents algorithm results for speech processed through low bit-rate codecs and subjected to bit errors due to impaired channel conditions. Output-based quality measures would be a valuable tool for monitoring performance of speech communication systems such as digital mobile radio networks and mobile satellite systems