automatic speech recognition造句
例句與造句
- Application of hmm in automatic speech recognition system
在語音識別系統(tǒng)中的應(yīng)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?qū)W生介紹自動語音識別這一快速發(fā)展中的領(lǐng)域。 - Results show that ann has a higher recognition rate and potential advantages in automatic speech recognition
研究結(jié)果表明，神經(jīng)網(wǎng)絡(luò)識別方法有較高的識別率和獨(dú)特的應(yīng)用優(yōu)勢。 - It's difficult to find automatic speech recognition in a sentence. 用automatic speech recognition造句挺難的
- The framework and functions of the system based on commercial automatic speech recognition ( asr ) engine are introduced
摘要介紹實(shí)現(xiàn)商用自動語音識別的系統(tǒng)架構(gòu)及其功能，闡述應(yīng)用自動語音識別技術(shù)實(shí)現(xiàn)的新通信增值業(yè)務(wù)。 - 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(jīng)被應(yīng)用的連續(xù)的和演講者無關(guān)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(shù)在當(dāng)代人們的生活中有了越來越廣泛的應(yīng)用。目前自動語音識別又大致分為連續(xù)語音識別和關(guān)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(tǒng)的噪聲魯棒性是決定語音識別技術(shù)從實(shí)驗(yàn)室走向?qū)嶋H應(yīng)用的關(guān)鍵環(huán)節(jié)，是目前語音識別領(lǐng)域的研究熱點(diǎn)與難點(diǎn)。 - 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(jī)交互系統(tǒng)的快速發(fā)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(lǐng)域。 - A general structure of speech control for intelligent electrical system is presented , which includes an operation platform for both automatic speech recognition ( asr ) and driver intention recognition ( dir ) and the intelligent electrical / electronic system in vehicles
摘要提出一種語音控制汽車智能電器系統(tǒng)的總體結(jié)構(gòu)框架，包括語音識別和駕駛員意圖識別的運(yùn)算平臺及汽車智能電器系統(tǒng)。 - The application of artificial neural networks ( ann ) to automatic speech recognition ( asr ) is investigated in this thesis . the recognition of speaker - independent and isolated words is focused and three types of ann model are presented . the related algorithms and programs are developed
本文基于自動語音識別( asr )的原理和過程，結(jié)合人工神經(jīng)網(wǎng)絡(luò)( ann )的建模理論及特點(diǎn)，主要研究了人工神經(jīng)網(wǎng)絡(luò)在自動語音識別中的應(yīng)用問題。 - Based on the theory and procedure of the automatic speech recognition ( asr ) ， and combined the theory and characteristics of the artificial neural networks ( ann ) ， the research in this paper is oriented on the theory and application of the mixed model ? hmmnn ， which is formed by the combination of the hidden markov model ( hmm ) and the self - organized neural networks （ sonn ） ， and the related algorithms and model are developed
本文基于自動語音識別（ asr ）的原理和過程，結(jié)合人工神經(jīng)網(wǎng)絡(luò)( ann )的建模理論及特點(diǎn)，主要研究了隱含馬爾可夫模型（ hmm ）與自組織神經(jīng)網(wǎng)絡(luò)( sonn )相結(jié)合的混合模型hmmnn的原理及在語音識別中的應(yīng)用，分析構(gòu)造了相應(yīng)的語音識別模型與算法。 - Fourthly , since the missing between training and practical environments is the fundamental reason for the degradation of performance of automatic speech recognition , we have proposed a method to compensate and amend hmm to adapt noise environments . experiments show that better noisy robustness can be achieved , especially in stationary background noisy environments
在語音特征參數(shù)級去噪的基礎(chǔ)上，提出了一種基于hmm和倒譜特征的噪聲補(bǔ)償方法，通過對純凈環(huán)境下的模型參數(shù)的補(bǔ)償與修正，實(shí)現(xiàn)訓(xùn)練環(huán)境與測試環(huán)境的匹配。 - Professor ching s research interests include adaptive digital signal processing , time delay estimation and target localization , wavelets , blind signal estimation and separation , automatic speech recognition for cantonese , speech modeling and speech synthesis , hands - free communications and advanced signal processing techniques for communications
程教授從事的研究包括信息技術(shù)、數(shù)字信號處理、語音分析合成、識別，以及陣列處理及通信等。他出版了一百六十多篇專文，先后于國際性期刊刊登及于國際會議中發(fā)表。