CAJ | 학술논문

提出了一种用语音转换技术改善电话语音识别性能的方法.通过模拟真实电话信道条件下影响语音质量的各种因素,实现由纯净语音到电话语音的转换.识别试验利用模拟电话语音评估了HMM识别器做MLLR自适应前后的性能.实验数据显示,自适应前由转换语音训练的模型识别率比由纯净语音训练的模型识别率增加了18.9%,而自适应试验表明,由转换语音训练而成的模型在MLLR自适应后,系统识别性能进一步得到改善,识别率增加了5.8%.识别实验表明所提语音转换方法可以减小由于真实电话语料缺乏而造成训练语音和测试语音声学性质的不匹配,从而有效地改善电话语音识别系统的性能.
제출료일충용어음전환기술개선전화어음식별성능적방법.통과모의진실전화신도조건하영향어음질량적각충인소,실현유순정어음도전화어음적전환.식별시험이용모의전화어음평고료HMM식별기주MLLR자괄응전후적성능.실험수거현시,자괄응전유전환어음훈련적모형식별솔비유순정어음훈련적모형식별솔증가료18.9%,이자괄응시험표명,유전환어음훈련이성적모형재MLLR자괄응후,계통식별성능진일보득도개선,식별솔증가료5.8%.식별실험표명소제어음전환방법가이감소유우진실전화어료결핍이조성훈련어음화측시어음성학성질적불필배,종이유효지개선전화어음식별계통적성능.
A study on speech conversion technology is addressed to improve the telephone speech recognition performance. The speech conversion method is implemented by simulating the influential factors in actual telephone connections. MLLR adaptations are conducted to evaluate the performances of the HMM recognizers, which are trained from the clean speech and generated data respectively. The results without adaptation report that the models trained on generated data can give an 18.9% higher recognition rate than those on clean speech. The adaptation results show that MLLR algorithm contributes an extra increase of 5.8% to the recognition rate of telephone speech system. The experiments illustrate that telephone speech recognition performance can be effectively improved using the generated data, and the conversion method can reduce the acoustic mismatch between the training and test data, which is induced by the shortage of the actual telephone speech.