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feature of speech

[网络] 演讲特点

网络

双语例句

  • One of the essential feature of intelligent human-machine interface is speech communication. So speech recognition has become an active research area.
    智能型人机界面的最基本特征是能进行人机的语音交互,因此语音识别成了当今研究的一大热门领域。
  • MFCC feature extraction of speech based on pitch period
    基于基音周期的语音MFCC参数提取
  • Searl considers the intentionality as the primary feature of speech act, holding that the illustration of language meaning is inseparable from intentionality.
    塞尔认为意向性是言语行为的基本特征,要想阐释语言的意义,必须研究意向性。
  • Speech recognition has wide use in the field of communication and so on. Speech feature parameter extraction is an important part of the speech recognition system.
    语音识别在通信等领域有着广泛的用途,其中语音特征参数提取是语音识别系统的一个重要组成部分。
  • The colloquialism is the most distinctive feature of the host's verbal speech and the host's gestures, which should conform to the plain, authentic, natural and friendly context, are closely associated with the host's refinement and creativity.
    播报的口语化是电视新闻节目主持人有声语体构成的最大特色,主持人的体态语体必须符合新闻节目朴素、真实、自然、亲切的语境,同时与主持人的内在修养和创造性密切相关。
  • According to the simulated results, the power spectrum of ARMA model is more accurate than that of AR model, which is more suitable to reflect the feature of speech signal. ( 4) ARMA model is used in CELP.
    由仿真可知,ARMA模型比AR模型的功率谱更加准确,更适合描述语音信号的特性。(4)将ARMA应用到CELP算法中。
  • For the length of feature vectors of speech samples is different, direct cutting and Dynamic Time Warping ( DTW) regulation, are put forward to solve the problem.
    提出了直接截取和DTW规正两种方法来解决语音样本特征向量长度不一致的问题。
  • On Feature Extraction Algorithm of Radar Object Based on Speech Processing
    基于语音处理的雷达目标特征提取算法研究
  • The feature distribution of speech and non-speech, and the form of change, are examined for speech detection.
    介绍和提出了一种基于x~2分布的突变检测和一种语音/非语音决策树;
  • During simulation experiment, wavelet analysis technique is adopted to extract feature vectors of speech, the results show that SVM and FSVM have both higher correct recognition rate and shorter training time than RBF network.
    在仿真实验中,采用小波分析方法提取语音特征向量,识别结果表明,SVM和FSVM比RBF网络具有较好的泛化性能,训练时间也大大缩减。