Discrete Choice Models for Non-Intrusive Quality Assessment
2011 (English)In: 12th Annual Conference Of The International Speech Communication Association 2011 (INTERSPEECH 2011), Vols 1-5, ISCA , 2011, 200-203 p.Conference paper (Refereed)
Non-intrusive signal quality assessment in general, and its application to speech signal processing, in particular, builds extensively upon statistical regression models. Commonly, the raw preference scores used for fitting these models belong to a categorical scale. Averaging the scores over a number of test subjects results in smooth, close-to-continuous ratings, thus justifying the use of regression as opposed to classification models. A form of marginalization, averaging subjective ratings takes away useful information about the reliability of individual test points. Using a model tailored to the raw data achieves highly competitive performance in terms of conventional performance measures while providing the additional advantage of identifying the usability of individual test points. In this paper, we consider the application of discrete choice models to non-intrusive quality assessment of speech.
Place, publisher, year, edition, pages
ISCA , 2011. 200-203 p.
, Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, ISSN 1990-9772
Discrete choice model, Distribution fitting, Non-intrusive quality assessment
IdentifiersURN: urn:nbn:se:kth:diva-113212ISI: 000316502200052ScopusID: 2-s2.0-84865733461ISBN: 978-1-61839-270-1OAI: oai:DiVA.org:kth-113212DiVA: diva2:587584
12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011; Florence; Italy; 27 August 2011 through 31 August 2011
ProjectsListening Talker (LISTA)
FunderEU, FP7, Seventh Framework Programme
QC 201305242013-01-142013-01-142013-12-13Bibliographically approved