NSQM: A non-intrusive assessment of speech quality using normalized energies of the neurogram

Jassim, Wissam A. and Zilany, Muhammad Shamsul Arefeen (2019) NSQM: A non-intrusive assessment of speech quality using normalized energies of the neurogram. Computer Speech & Language, 58. pp. 260-279. ISSN 0885-2308, DOI https://doi.org/10.1016/j.csl.2019.04.005.

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Official URL: https://doi.org/10.1016/j.csl.2019.04.005


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. © 2019

Item Type: Article
Funders: Grants UM.C/625/1/HIR/152, RP016B-13AET, and UM.C/625/1/HIR/MOHE/ENG/42 from University of Malaya, Grant FRA-470192-25145 from the Texas A&M University at Qatar, Grant 13/RC/2106 from the ADAPT Centre for Digital Content Technology, Trinity College Dublin under the SFI Research Centres Programme
Uncontrolled Keywords: Speech quality assessment; PESQ; POLQA; Neurogram; Auditory-nerve model; Discrete Wavelet transform
Subjects: R Medicine
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 03 Apr 2020 05:17
Last Modified: 03 Apr 2020 05:17
URI: http://eprints.um.edu.my/id/eprint/24134

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