feature of speech
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双语例句
- 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。 - 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 - 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 system performance of dialect identification depends on feature extraction of the speech signal, and the reasonable selection of characteristic parameters can greatly improve the recognition rate on dialect identification system.
方言辨识系统性能好坏取决于语音信号特征的提取，合理地选择特征参数对方言辨识系统的识别率有很大的提高。 - 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。 - Then the influence of the weighting of feature vectors, the time duration of speech segments and the various choose of factor α on the performance of a small open-set text-independent speaker identification system is researched by experiments.
在小规模说话人辨认系统的实验研究中，研究了特征矢量的加权、语音段的时长以及α因子的选择对系统性能的影响。 - Study on Robust Feature Extraction Method of Speech and Audio-based Context Recognition
稳健语音特征和音频场景识别方法的研究 - ( 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。 - 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。 - 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。