In this thesis , first we analyzed and designed a traditional continued speech recognition system , which based on hmm and mfcc speech features . then we researched some noise robust technologies based on that system 本论文首先分析并实现了一个以mel频率倒谱系数( mfcc )作为语音特征,基于隐马尔可夫模型( hmm ) ,针对连续数字串识别任务的基本连续语音识别系统。
The study on the speech emotion recognition has found very important realistic values in such aspects as enhancing the intelligence and humanity of computer , developing new human - machine environment , improving speech recognition results 语音情感识别的研究对于增强计算机的智能化和人性化,开发新型人机环境,以及提高语音识别系统的性能等方面,均有着非常重要的现实意义。
At last , we propose a new speech recognition method which combines ras - mfccs and mmse speech enhancement technology . experimental results show that this method improves the performance of ras - mfccs in lower snr and outperforms mmse speech enhancement 实验结果表明,这种相结合的方法能有效地提高语音识别系统的识别率,并且在低信噪比情况下仍能使系统保持相当高的识别率。
This paper is with the purpose of realizing a city road name speech recognition system based on hmm model . this paper has introduced the thought as well as the improvement in the algorithm of speech recognition in realizing high recognition rate in detail 本文以最终实现一个基于hmm模型的城市道路名语音识别系统为目的，详细介绍了作者在实现高识别率的语音识别算法中的思想以及改进。
Prevailing speech recognition systems can obtain a very high accuracy for clean speech recognition , but their performance will degrade rapidly in noisy environments owing to the mismatch between the acoustic models and the testing speech 目前的语音识别系统对纯净语音可以达到非常高的识别精度，但是无处不在噪声带来了训练模型和测试语音之间的失配，识别器的性能在噪声环境中将会急剧下降。
Prevailing speech recognition systems can obtain a very high accuracy for clean speech recognition , but their performance will degrade rapidly in noisy environments owing to the mismatch between the acoustic models and the testing speech 目前的语音识别系统对干净语音可以达到非常高的识别精度,但是无处不在的噪声带来了训练模型和测试语音之间的失配,造成识别器的性能在噪声环境下急剧地下降。
4 . speech enhancement techniques are applied to the speech recognition system in this thesis . the experiment results show that after the combination of the two systems , the output snr of the noise speech is improved and the recognition rate is enhanced 4 .将语音增强技术与语音识别系统结合起来,即通过对原始带噪语音进行语音增强处理,提高信号的信噪比和可懂度,从而提高语音识别系统的识别率。
