| 1. | Application of hmm in automatic speech recognition system
在语音识别系统中的应用 |
| 2. | Asr automatic speech recognition
自动语音识别 |
| 3. | Automatic speech recognition
自动语音识别 |
| 4. | 345 introduces students to the rapidly developing field of automatic speech recognition
345向学生介绍自动语音识别这一快速发展中的领域。 |
| 5. | Results show that ann has a higher recognition rate and potential advantages in automatic speech recognition
研究结果表明，神经网络识别方法有较高的识别率和独特的应用优势。 |
| 6. | The framework and functions of the system based on commercial automatic speech recognition ( asr ) engine are introduced
摘要介绍实现商用自动语音识别的系统架构及其功能，阐述应用自动语音识别技术实现的新通信增值业务。 |
| 7. | Since hmm was introduced at the end of 1960 , it has been applied to the connected , speaker - independent , automatic speech recognition with the advantage of modeling various patterns
在1960年末被提出的hmm模型，已经被应用的连续的和演讲者无关的自动演讲识别中。 |
| 8. | Automatic speech recognition is used more and more widely in people ’ s life , which is categorized into continuous speech recognition and keyword spotting
自动语音识别技术在当代人们的生活中有了越来越广泛的应用。目前自动语音识别又大致分为连续语音识别和关键词识别。 |
| 9. | The noise robustness is one of the crucial factors that have deep influence upon the practicability of the speech recognition system , and then it has become the focus in the research field of automatic speech recognition
语音识别系统的噪声鲁棒性是决定语音识别技术从实验室走向实际应用的关键环节，是目前语音识别领域的研究热点与难点。 |
| 10. | Along with rapid development of human computer interaction system , emotion in speech is a topic that has received much attention during the last few years , in the context of speech synthesis as well as in automatic speech recognition
随着人机交互系统的快速发展,语音信号中的情感信息近年来正越来越受到人们的重视,特别是在语音合成和语音识别等领域。 |
