语音信号自动识别系统对语音信号退化因素的鲁棒性分析

J. Oska, J. Wojtun, K. Wodecki, Z. Piotrowski
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引用次数: 0

摘要

本文给出了在G.711、G.723.1和iLBC编解码器中使用有损压缩对孤立语音短语识别效率影响的研究结果。在研究中比较了音频信号参数化方法LPCC和MFCC(线性预测倒谱系数,Mel频率倒谱系数)对退化因子的鲁棒性。本研究基于改进的高斯混合分类器,并考虑通用背景模型GMM-UBM(高斯混合模型-通用背景模型)。该研究是在由3000个孤立的语音短语组成的数据库上进行的。
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Robustness analysis of automatic speech signal recognition system against factors degrading speech signal
In the article there are presented the results of research on the influence of the lossy compression, used in codecs G.711, G.723.1 and iLBC, on the efficiency of isolated speech phrase recognition. In the research the degree of robustness against degrading factors in the parameterisation method of audio signal LPCC and MFCC (Linear Prediction Cepstral Coefficients, Mel Frequency Cepstral Coefficients) is compared. The research is based on the classifier of improved Gaussian mixtures making allowance for Universal Background Model GMM-UBM (Gaussian Mixtures Model - Universal Background Model). The research was conducted on the database composed of 3000 isolated speech phrases.
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