基于梅尔频率倒谱系数的语音清晰度DRT识别
Speech Articulation DRT Recognition Based On Mel Frequency Cepstral Coefficient
马成龙 1焦俊清 1焦富清 1王杰 1陈巧特 1谢武俊 2李军2
作者信息
- 1. 武汉普创数据科技有限公司,武汉,430205
- 2. 航宇救生装备有限公司,襄阳,441058
- 折叠
摘要
语音清晰度在通信终端、设备系统语音识别方面具有重要意义.本文对110dB噪声干扰下采集到的语音信号进行谱减法降噪,双门限端点检测提取发音字段,然后提取梅尔频率倒谱系数(MFCC),再将其进行差分计算,得到一阶和二阶分量,结合短时能量作为语音信号的特征参数,最后通过动态时间归整(DTW)进行相似度识别.实验表明,本文算法对汉语清晰度诊断押韵测试(DRT)字表的测试结果高达92.90％,有良好的识别率.
Abstract
Speech articulation plays an important role in speech recognition of communication terminals and equipment systems.In this paper,under the interference of 110 dB noise,the collected speech signal is de-noised by spectral subtraction,the pronunciation field is extracted by double-threshold endpoint detection,and then the Mel Frequency Cepstral Coefficients(MFCC)is extracted,and the difference calculation is carried out to obtain the first-order and second-order components,and the short-time energy is used as the characteristic parameter of the speech signal.Finally,Dynamic Time Warping(DTW)is used for similarity recognition.The experimental results show that the algorithm has a high recognition rate of 92.90％for Chinese articulation Di-agnostic Rhyme Test(DRT).
关键词
语音清晰度/谱减法/端点检测/梅尔频率倒谱系数/动态时间归整/汉语清晰度诊断押韵测试Key words
speech articulation/spectral subtraction/endpoint detection/Mel Frequency Cepstral Coeffi-cients/Dynamic Time Warping/Diagnostic Rhyme Test引用本文复制引用
出版年
2024
NETL
NSTL
万方数据