摘要
频谱和倒谱的联合调整方法,用于对语音识别中信道差异和背景噪音的存在进行联合补偿。该方法根据干净语音的最大似然准则在频域和倒谱域分别对噪音和信道进行补偿,避免了对噪音和信道影响模型进行简化所带来的误差影响,且实现时间复杂度较低。在信噪比由10dB到20dB的含有信道和加性噪音的汉语数字串识别实验中,该方法使平均音节错误率相对下降了50．44%。实验表明频谱和倒谱的联合调整方法可以快速的补偿信道差异和背景噪音。
A method named spectral and cepstral joint adjusting was proposed in order to jointly compensate for the channel mismatch and existence of additive noise in speech recognition. The method compensates for the noise and channel mismatch in spectral and cepstral domain respectively based on the ML rule. It didn＇t simplify the model of channel and noise effect on speech, and therefore reduce the error brought by the model simplification. Furthermore, the time complicacy was relatively low. The experiment on noisy Chinese digit string recognition with SNR of 10 dB to 20 dB was carried out. The results showed that the proposed method obtained the relative error rate reduction of 50.44%, which indicated that the spectral and cepstral joint adjusting method could rapidly compensate for the channel and noise well.
出处
《声学学报》
EI
CSCD
北大核心
2006年第5期466-470,共5页
Acta Acustica
基金
863计划项目(2001AA114071)
关键词
背景噪音
语音识别
信道
补偿
最大似然准则
时间复杂度
汉语数字串
误差影响
Acoustic noise
Communication channels (information theory)
Error compensation
Mathematical models
Signal to noise ratio
