Speaker Recognition Improvement Using Blind Inversion Of Distortions

descriptionPublicationkeyboard_double_arrow_right Conference object , Article , Preprint 06 Sep 2004Embargo end date: 01 Mar 2022 Spain Publisher:ZenodoJournal:CoRR, volume abs/2203.01164

Authors: Marcos Faúndez-Zanuy; Jordi Solé-Casals;

doi: 10.5281/zenodo.38214 , 10.48550/arxiv.2203.01164

arXiv: 2203.01164

handle: 10854/2802

Speaker Recognition Improvement Using Blind Inversion Of Distortions

- Summary
- Subjects
- Metrics

Abstract

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results shows that a combination of data fusion with and without nonlinear distortion compensation can improve the recognition rates with saturated test sentences from 80% to 88.57%, while the results with clean speech (without saturation) is 87.76% for one microphone.

4 pages

Country

Spain

Related Organizations

University of Vic
Spain

Keywords

Veu, Processament de, FOS: Computer and information sciences, Computer Science - Machine Learning, Sound (cs.SD), Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, Machine Learning (cs.LG)

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average