feature of speech
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[网络] 演讲特点
双语例句
- Using the invariable characteristics of PCNN time series and entropy series of Spectrogram, people can extract the feature of speakers speech and recognize the speakers rapidly and effectively.
该方法将语谱图输入到PCNN后得到输出图像的时间序列及其熵序列作为说话人语音的特征，利用它的不变性实现说话人识别。 - This paper uses wavelet theory in noise-robust feature extraction of speech recognition and introduces a feature extraction method based on Gauss wavelet filter. The Gauss wavelet filter with human critical frequency band is obtained by studying human auditory characteristics.
把小波理论应用于抗噪语音识别特征提取，提出了基于高斯小波滤波器的语音识别特征提取方法，通过对人耳听觉特性的研究，按照人耳临界带宽设计了一组高斯小波带通滤波器。 - First of all, I analyse the prosodic feature of the news broadcasting speech with the knowledge of acoustic-phonetics. For example, the extending of the syllable duration is the acoustic characteristics of the pre-boundary syllables and the accented syllables.
首先，通过实验的手段分析了新闻播音语言韵律特征的语音声学表现：即音节时长的拉长是边界前音节和重音音节的声学征兆； - 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。 - Extraction and Analysis of the Feature of Complex Wavelet Speech Spectrogram Based on Mathematical Morphology
基于数学形态学的复子波语音谱图特征提取与分析 - Design and analysis of acoustic feature for corpus of speech synthesis
语音合成语料库的设计与声学特征分析 - 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。 - Difference technology can express the dynamic feature parameters of speech.
差分技术可以体现语音特征参数的动态特征。 - 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。 - A Study on the Essential Feature of Speech Signals
语音信号基本载体的研究