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1下载：
matalb听觉处理工具箱,很多关于听觉和语音信号处理的有用函数,值得参考.-matalb auditory processing toolbox, a lot of hearing and speech signal processing useful function, a good reference.
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关于语音增强的一些算法心得，如谱减法自适应滤波以及听觉掩蔽效应等。-on speech enhancement algorithms some experiences, such as spectral subtraction adaptive filtering and auditory masking effect.
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MFCC参数很好的反映了人耳的听觉特性,所以在语音识别中我们也用到他,本代码是用matlab仿真了MFCC 参数的提取过程.-MFCC parameters well reflected the auditory characteristics of the human ear, so in speech recognition, we also used him, and this code is used matlab simulation parameters of the MFCC ex
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论文首先介绍了传统的语音特征参数MFCC，它是基于人耳听觉
特性设计的一种特征参数，在静音环境下能得到较高的识别率，但在
信噪比较低时识别率急剧下降，不利于实用化。本文通过对MFCC算
法的分析和研究，发现其中的FFT和DCT在整个时频空间使用固定的
。分析窗，这不符合语音信号特性，而小波变换具有多分辨率特性，更
符合人耳的听觉特性。因此，本文将小波变换和MFCC算法相结合，
提出了三种新的语音识别特-Speech recognition has wide use in
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语音识别相关的sci论文，包括
Production and perception of speaker-specific phonetic detail
Self-learning speaker identification for enhanced speech recognition
Sources ofillusioninconsonantclusterperception
Speech listening specifically modulates the exci
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音响设备接口（SDI）是专为听觉显示，或AUI（音频用户界面），这已被证明是很好的补充GUI（图形用户界面）学术。目前，SDI实现两个Sound对象：语音和听觉符号为例。言语是在3D世界中的定位语音合成相结合的ViaVoice TTS和，A3D一起。在学术上，这种定位可以帮助用户挑选出所需要的信息，两个同时“显示”的声音。这是所谓的“鸡尾酒会效应”。此外，它可以提高存储器中，添加的位置系数对每一个声音。听觉符号为例，从字面上看，可以显示听觉符号为例容易。听觉符号为例是怎么样的音乐modif，图标
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SDI(Sound Device Interface) is designed for Auditory Display, or AUI(Audio User Interface), which has proved to be good complement to GUI(Graphic User Interface) academically. the SDI implements two Sound Object: Speech and Earcon. Speech is for posi
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一种低复杂度的基于听觉感知的高效心理声学模型语音质量客观评估算法，目前已经被ITU-T标准采纳为P.862标准，
对大家深入理解P.862标准有很大的帮助，在学术工作者和从事这方面的工作工程技术人员都很有用-An efficient auditory perception based psychoacoustic model objective speech quality assessment of low complexity algorithms, has now been adopt
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2基于噪声估计和听觉掩蔽效应的语音增强.pdf-2 speech and auditory masking noise estimation based enhancements. Pdf
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这是一篇期刊。里面详细介绍了一种将多频带谱减和听觉掩蔽系统结合的语音增强算法，增强效果比较好，可供大家参考学习。-This is a journal. Which details a multi-band spectral subtraction and auditory masking system combines speech enhancement algorithms to enhance better, for your reference study.
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Signal processing front end for extracting the feature
set is an important stage in any speech recognition
system. The optimum feature set is still not yet
decided. There are many types of features, which are
derived differently and have good
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于市售 STM32 开发板上实现特定人语音识别处理项目。识别流程是：预滤波、ADC、分帧、端点检测、预加重、加窗、特征提取、特征匹配。端点检测(VAD)采用短时幅度和短时过零率相结合。检测出有效语音后，根据人耳听觉感知特性,计算每帧语音的 Mel 频率倒谱系数(MFCC)。然后采用动态时间弯折(DTW)算法与特征模板相匹配,最终输出识别结果。先用Matlab对上述算法进行仿真，经数次试验求得算法内所需各系数的最优值。而后将算法移植到 STM32 开发板上，移植过程中根据 STM32 上存储空间相
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语音分析与处理，praat处理与应用，声学分析与处理，praat操作与应用。(Acoustic phonetics is a subfield of phonetics, which deals with acoustic aspects of speech sounds. Acoustic phonetics investigates time domain features such as the mean squared amplitude of a waveform, its durat
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语音处理工具箱，里面含有几乎所有的程序，处理语音的所有的函数(This toolbox will be useful to researchers that are interested in how the auditory
periphery works and want to compare and test their theories. This toolbox will also be useful to speech and auditory engineers who want
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This toolbox will also be useful to speech and auditory
engineers who want to see how the human auditory system represents sounds.
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This toolbox will also be useful to speech and auditory
engineers who want to see how the human auditory system represents sounds.
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