ISCA Archive Interspeech 2009
ISCA Archive Interspeech 2009

A non-intrusive signal-based model for speech quality evaluation using automatic classification of background noises

Adrien Leman, Julien Faure, Etienne Parizet

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.


doi: 10.21437/Interspeech.2009-332

Cite as: Leman, A., Faure, J., Parizet, E. (2009) A non-intrusive signal-based model for speech quality evaluation using automatic classification of background noises. Proc. Interspeech 2009, 1139-1142, doi: 10.21437/Interspeech.2009-332

@inproceedings{leman09_interspeech,
  author={Adrien Leman and Julien Faure and Etienne Parizet},
  title={{A non-intrusive signal-based model for speech quality evaluation using automatic classification of background noises}},
  year=2009,
  booktitle={Proc. Interspeech 2009},
  pages={1139--1142},
  doi={10.21437/Interspeech.2009-332}
}