ArticleEURASIP journal on audio, speech, and music processing2012
Biomimetic multi-resolution analysis for robust speaker recognition.
Article in EURASIP journal on audio, speech, and music processing, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A Framework for Speech Activity Detection Using Adaptive Auditory Receptive Fields.IEEE/ACM transactions on audio, speech, and language processing · 2015Article
- Recognizing the message and the messenger: biomimetic spectral analysis for robust speech and speaker recognition.International journal of speech technologyArticle
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Authors and funding
4 authors.
Funding
Abstract
Humans exhibit a remarkable ability to reliably classify sound sources in the environment even in presence of high levels of noise. In contrast, most engineering systems suffer a drastic drop in performance when speech signals are corrupted with channel or background distortions. Our brains are equipped with elaborate machinery for speech analysis and feature extraction, which hold great lessons for improving the performance of automatic speech processing systems under adverse conditions. The work presented here explores a biologically-motivated multi-resolution speaker information representation obtained by performing an intricate yet computationally-efficient analysis of the information-rich spectro-temporal attributes of the speech signal. We evaluate the proposed features in a speaker verification task performed on NIST SRE 2010 data. The biomimetic approach yields significant robustness in presence of non-stationary noise and reverberation, offering a new framework for deriving reliable features for speaker recognition and speech processing.
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Registered trials
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