Speech Quality Perception and its Estimation

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Assessment of speech quality is an important topic in a number of fields including telecommunications, Audiology, and Speech Pathology . For example, speech quality measurements are used to benchmark the performance of speech coding, noise reduction and echo suppression algorithms in telecommunications. Similarly, speech quality is an important factor in users' acceptance of and satisfaction with hearing aids and assistive listening devices. Likewise, speech quality measures are useful in quantifying the severity of a speech/voice disorder and in monitoring therapy progress. A good speech quality measure is therefore an important parameter that will allow efficient evaluation of communication and hearing devices, as well as assist in speech/voice disorder therapeutic management.Speech quality can be assessed through objective or subjective means. While subjective opinions ofspeech quality are preferred as the most trustworthy criteria, they are also time-consuming and expensive. Therefore, computational methods that predict subjective speech quality score with reasonable accuracy are attractive and form the focus of our research work.During the past few years, we have developed novel features for compact representation of speech quality. In addition, we have developed a neuro-fuzzy feature mapper and a Bayesian multivariate linear splines regressor to map these feature vectors into speech quality scores. Our techniques have been successfully applied to problems in telecommunications, Audiology, and Speech Pathology fields. We plan to build upon our work during the next five years by investigating more effective feature extraction and feature mapping schemes, byincorporating new models of impaired hearing in predicting the impact of hearing aid signal processing algorithms on perceived speech quality, and by developing new methodologies for instrumental assessment of abnormal voice quality.