Using redundant parallel architecture to improve speaker recognition performance
Zhengquan QIU
Junxun YIN
Caiyun FAN
摘要：In this Paper, we propose two kinds of modifications in speaker recognition.First,the correlations between frequency channels are of prime importance for speaker recognition.Some of these correlations are lost when the frequency domain is divided into sub-bands.Consequently we propose a particularly redundant parallel architecture for which most of the correlations are kept.Second,generally a log transformation used to modify the power spectrum is done after the filter-bank in the classical spectrum calculation.We will see that performing this transformation before the filter bank is more interesting in our case.In the processing of recognition,the Gaussian mixture model(GMM)recognition arithmetic is adopted.Experiments on speech corrupted by noise show a better adaptability of this approach in noisy environments,compared with a conventional device,especially when pruning of some recognizers is performed.
机标关键词：
分类号：TP3(计算技术、计算机技术)
资助基金：国家自然科学基金(60171043)国家自然科学基金(60371046)
论文发表日期：2008-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：3( 221-223 )
英文信息