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- Research of Overlapping Speech Signals Separation Based on CASA 基于声场景分析的混叠语音分离研究
- speech signal separation 语音分离
- Yinmarkerf development kit for the analysis and recognition of speech signal. 隐马尔科夫工具开发包,用于语音信号的分析和识别。
- Nowadays the VAD is a hot spot in the speech signal processing field. 本论文研究复杂强背景噪声下的语音信号检测问题。
- Firstly calculate the absolution of the source speech signal, then analyze the absoluted signal in the dyadic wavelet domain. 首先对原始语音信号取绝对值,然后对其进行小波变换,认为8阶小波变换绝对值的极大值点对应于原始语音的音素分段点。
- Almost all of the basic algorithm code in speech signal processing. Welcome to download. 详细说明:语音信号处理中的所有基本的算法的代码,很全的。欢迎大家下载使用
- Blind signal separation (BSS) is a new powerful technique in modern signal processing. 盲分离(Blind signal separation,BSS)技术是现代信号处理领域中一个崭新的研究方向。
- According to the formant frequency of speech signal, the striations are existed in their spectrograms. 在办公室的环境里,存在冷气或电风扇运转的背景环境噪音;
- A new method of blind signal separation was provided to achieve FECG (Fetal ECG) detection. 本文提出了用盲信号分离提取胎儿心电的方法。
- Dereverberation of speech signal is applied to many areas including communication and speech recognition. 摘要语音信号去混响技术在通信、语言识别等方面有重要应用。
- A multi-channel acoustic echo suppression model(MCAESM) via second-order blind signal separation(BSS) is proposed. 本文提出了一个基于二阶盲信号分离的多路声回波抑制模型。
- All traditional methods for speech detection need sensors nearby the human body to detect the speech signal. 传统的语音检测方法均需要通过人体附近的传感器来检测语音信号。
- In this paper, we present how to reconstruct original speech signal from Correlogram of auditory model. 摘要研究如何从听觉模型的自相关谱中恢复出原始的声音信号。
- As a branch of BSP, Blind source separation, or source signal separation (BSS), has also become a powerful tool in the areas of signal an. 盲源分离是一个很独特的盲信号分析与处理工具,在机械设备状态监测与故障诊断领域有较好的应用前景。
- The speech signal is a analog one, and we can perform its digital transmission by sampling, quantizing and coding. 话音信号是一个模拟信号,通过采样、量化和编码,我们可以实现话音信号的数字传输。
- Indeterminacies in amplitude and permutation are the two main cumbersome aspects in frequency domain blind signal separation. 排序和幅度不一致性是信号频域盲源分离的主要困难。
- Pitch period is an important parameter of speech signal,and it has been applied in many domains. 基音周期是语音信号的一个重要参数,它在多个领域有着广泛的应用。
- T.F.Quatieri, Discrete-Time Speech Signal Processing Principles and Practice, Prentice hall PTR,2002. 李昌立,吴善培,“数字语音-语音编码实用教程”,人民邮电出版社,2004年
- Indeterminacies in amplitude and permutation are the two main cumbersome aspects for blind signal separation in frequency domain. 摘要排序和幅度不一致性是在频域进行信号盲源分离的主要困难。
- Whereupon speech signals are adapted as if come from the training set. 在语音识别领域,与说话人无关(SI)的识别方法需要大量的训练数据。