10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

A Non-Intrusive Signal-Based Model for Speech Quality Evaluation Using Automatic Classification of Background Noises

Adrien Leman (1), Julien Faure (1), Etienne Parizet (2)

(1) Orange Labs, France
(2) LVA, France

This paper describes an original method for speech quality evaluation in the presence of different types of background noises for a range of communications (mobile, VoIP, RTC). The model is obtained from subjective experiments described in [1]. These experiments show that background noise can be more or less tolerated by listeners, depending on the sources of noise that can be identified. Using a classification method, the background noises can be classified into four groups. For each one of the four groups, a relation between loudness of the noise and speech quality is proposed.

Full Paper

Bibliographic reference.  Leman, Adrien / Faure, Julien / Parizet, Etienne (2009): "A non-intrusive signal-based model for speech quality evaluation using automatic classification of background noises", In INTERSPEECH-2009, 1139-1142.