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Noise adaptation system for a speech model, a process for the noise adaptation and program for noise adaptation for speech recognition

机译:用于语音模型的噪声自适应系统,用于噪声自适应的过程和用于语音识别的噪声自适应程序

摘要

PROBLEM TO BE SOLVED: To perform optimum clustering processing for many noise data and to estimate a speech model series for an input speech more accurately.;SOLUTION: A clustering result is obtained by generating a noise-superposed speech (step S1) by superposing noise on a speech under a noise-to-signal ratio condition, performing processing (step S2) wherein a mean value of speech cepstrum is subtracted as to the generated noise-superposed speech, generating a Gauss distribution model of respective noise-superposed speeches (step S3), and calculating likelihood between noise-superposed speeches and generating a likelihood matrix (step S4). An optimum model is selected (step S7) and linear conversion (step S8) is carried out so that the likelihood becomes maximum. A clustering stage and a model learning stage are applied to the noise-superposed speeches, so clustering processing of many noise data and accurate speech model series estimation can be realized.;COPYRIGHT: (C)2005,JPO&NCIPI
机译:要解决的问题:对许多噪声数据进行最佳聚类处理,并更准确地估计输入语音的语音模型系列。解决方案:通过叠加噪声生成叠加了噪声的语音(步骤S1)来获得聚类结果对在信噪比条件下的语音进行处理(步骤S2),其中针对所生成的叠加有噪声的语音减去语音倒谱的平均值,从而生成各个叠加有噪声的语音的高斯分布模型(步骤S2)。 S3),并计算噪声叠加语音之间的似然度并生成似然度矩阵(步骤S4)。选择最佳模型(步骤S7),并进行线性转换(步骤S8),以使可能性变为最大。通过对噪声叠加的语音进行聚类和模型学习,可以实现许多噪声数据的聚类处理和准确的语音模型序列估计。;版权所有:(C)2005,JPO&NCIPI

著录项

  • 公开/公告号DE602004000716T2

    专利类型

  • 公开/公告日2007-05-03

    原文格式PDF

  • 申请/专利权人

    申请/专利号DE20046000716T

  • 发明设计人

    申请日2004-03-04

  • 分类号G10L15/20;

  • 国家 DE

  • 入库时间 2022-08-21 20:28:11

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