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Title: Automatic speaker recognition with Multi-resolution Gaussian Mixture models (MR-GMMs)
Authors: D’Almeida, Frederico Quadros
Nascimento, Francisco Assis de Oliveira
Berger, Pedro de Azevedo
Silva, Lúcio Martins da
Assunto:: Reconhecimento automático da voz
Sistemas de processamento da fala
Voz codificada - engenharia elétrica
Issue Date: 2009
Publisher: Brazilian Association of High Technology Experts (ABEAT)
Citation: D'ALMEIDA, Frederico Quadros et al. Automatic speaker recognition with multi-resolution gaussian mixture models (mr-gmms). The International Journal of Forensic Computer Science v. 4, n. 1, p. 9-21, 2009. Disponível em: <http://www.ijofcs.org/abstract-v04n1-pp01.html>. Acesso em: 19 jun. 2012.
Abstract: Gaussian Mixture Models (GMMs) are the most widely used technique for voice modeling in automatic speaker recognition systems. In this paper, we introduce a variation of the traditional GMM approach that uses models with variable complexity (resolution). Termed Multi-resolution GMMs (MR-GMMs); this new approach yields more than a 50% reduction in the computational costs associated with proper speaker identification, as compared to the traditional GMM approach. We also explore the noise robustness of the new method by investigating MR-GMM performance under noisy audio conditions using a series of practical identification tests.
Licença:: Disponível sob Licença Creative Commons 3.0, que permite copiar, distribuir e transmitir o trabalho, desde que seja citado o autor e licenciante. Não permite o uso para fins comerciais nem a adaptação desta.
DOI: https://dx.doi.org/10.5769/J200901001
Appears in Collections:CIC - Artigos publicados em periódicos
ENM - Artigos publicados em periódicos

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