NSQM: A non-intrusive assessment of speech quality using normalized energies of the neurogram. (November 2019)

• Record Type: Journal Article
• Authors: Jassim, Wissam A.; Zilany, Muhammad S.
• Is Part Of: Computer speech & language. Volume 58(2019)
• Page Start: 260
• Page End: 279
• Publication Date: 2019-11
• Subjects: Speech quality assessment -- PESQ -- POLQA -- Neurogram -- Auditory-nerve model -- Discrete Wavelet transform; Speech processing systems -- Periodicals; Automatic speech recognition -- Periodicals; Computers -- Periodicals; Linguistics -- Periodicals; Speech-Language Pathology -- Periodicals; Traitement automatique de la parole -- Périodiques; Reconnaissance automatique de la parole -- Périodiques; Automatic speech recognition; Speech processing systems; Electronic journals; Periodicals; 006.454
• DOI: 10.1016/j.csl.2019.04.005
• Languages: English
• ISSNs: 0885-2308

Abstract

Abstract: This study proposes a new non-intrusive measure of speech quality, the neurogram speech quality measure (NSQM), based on the responses of a biologically-inspired computational model of the auditory system for listeners with normal hearing. The model simulates the responses of an auditory-nerve fiber with a characteristic frequency to a speech signal, and the population response of the model is represented by a neurogram (2D time-frequency representation). The responses of each characteristic frequency in the neurogram were decomposed into sub-bands using 1D discrete Wavelet transform. The normalized energy corresponding to each sub-band was used as an input to a support vector regression model to predict the quality score of the processed speech. The performance of the proposed non-intrusive measure was compared to the results from a range of intrusive and non-intrusive measures using three standard databases: the EXP1 and EXP3 of supplement 23 to the P series (P.Supp23) of ITU-T Recommendations and the NOIZEUS databases. The proposed NSQM achieved an overall better result over most of the existing metrics for the effects of compression codecs, additive and channel noises.