feature of speech
英
美
[网络] 演讲特点
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。 - In the new model is established, the speech recognition system, the selection of the speech signal of speech signal feature extraction and recognition of speech signal analysis.
在新的模型下，建立了语音分析识别系统，对所选取的语音信号进行特征参数提取和语音信号分析识别。 - And then introduces the functions and key technologies of pre-processing 、 feature extraction pattern matching and post-processing of speech recognition. Improved methods have been proposed in view of problems existed in traditional methods.
然后分别介绍了语音识别的预处理、特征参数提取、模式匹配和后处理阶段的功能及其关键技术，并针对传统方法中存在的问题提出了改进方案。 - 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。 - 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； - 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。 - Emotional Feature Analysis and Emotion Recognition of Speech
语音信号中情感特征的分析和识别 - ( linguistics) pertaining to a feature of speech that extends over more than a single speech sound.
（语言学）与语音特征有关系的超语段语音。 - A Study on the Essential Feature of Speech Signals
语音信号基本载体的研究 - 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；