Speech quality objective assessment using neural network

This paper presents a novel method for objective assessment of speech quality based on one-step strategy using a feedfoward neutral network. Currently, almost all the existing methods for this assessment can be regarded as a two-step strategy, requiring a distortion computation and a mapping from the average distortion value to the Mean Opinion Score (MOS). Our new method combines these two steps by means of a neural network which can incorporate the perception properties of the human auditory system and provide MOS estimate directly. Our theoretical analysis and experimental results suggest that this method of MOS estimate significantly overperforms the traditional methods. The correlation coefficient between the subjective test score and objective MOS estimate can reach up to about 0.95.