Application of hmm in automatic speech recognition system 在語音識別系統中的應用
Asr automatic speech recognition 自動語音識別
Automatic speech recognition 自動語音識別
345 introduces students to the rapidly developing field of automatic speech recognition 345向學生介紹自動語音識別這一快速發展中的領域。
Results show that ann has a higher recognition rate and potential advantages in automatic speech recognition 研究結果表明,神經網絡識別方法有較高的識別率和獨特的應用優勢。
The framework and functions of the system based on commercial automatic speech recognition ( asr ) engine are introduced 摘要介紹實現商用自動語音識別的系統架構及其功能,闡述應用自動語音識別技術實現的新通信增值業務。
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,已經被應用的連續的和演講者無關的自動演講識別中。
Automatic speech recognition is used more and more widely in people ’ s life , which is categorized into continuous speech recognition and keyword spotting 自動語音識別技術在當代人們的生活中有了越來越廣泛的應用。目前自動語音識別又大致分為連續語音識別和關鍵詞識別。
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 語音識別系統的噪聲魯棒性是決定語音識別技術從實驗室走向實際應用的關鍵環節,是目前語音識別領域的研究熱點與難點。
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 隨著人機交互系統的快速發展,語音信號中的情感信息近年來正越來越受到人們的重視,特別是在語音合成和語音識別等領域。