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[Speech/Voice recognition/combineImprovements in Speech Synthesis

Description: 语音识别的原理和应用以及语音系统的提高等知识-Fundamentals of voice recognition and its applications. And some knowledge about enhancement of voice system or so.
Platform: | Size: 3623719 | Author: sff | Hits:

[File Operatekalmanfilte221

Description: 语音合成与识别,适合非平稳信号,卡尔曼滤波用于语音增强算法,matlab,-speech synthesis and recognition, suitable for non-stationary signals, Kalman filtering algorithms for speech enhancement, Matlab,
Platform: | Size: 8959 | Author: 罗成 | Hits:

[Other resourcematsig-0.2.4

Description: 用于语音识别语音增强方面的matlab工具包,非常值得参考-for Speech Recognition speech enhancement of Matlab tool kit is very worthwhile reference! !
Platform: | Size: 193763 | Author: 袁坤 | Hits:

[Speech/Voice recognition/combineImprovements in Speech Synthesis

Description: 语音识别的原理和应用以及语音系统的提高等知识-Fundamentals of voice recognition and its applications. And some knowledge about enhancement of voice system or so.
Platform: | Size: 3623936 | Author: sff | Hits:

[Speech/Voice recognition/combinecdhmm

Description: 语音识别与合成的书籍,可以帮助你了解语音信号处理的基本知识-speech recognition and synthesis of books, I can help you find the voice signal processing basic knowledge
Platform: | Size: 55296 | Author: 樊星 | Hits:

[File Operatekalmanfilte221

Description: 语音合成与识别,适合非平稳信号,卡尔曼滤波用于语音增强算法,matlab,-speech synthesis and recognition, suitable for non-stationary signals, Kalman filtering algorithms for speech enhancement, Matlab,
Platform: | Size: 9216 | Author: 罗成 | Hits:

[matlabmatsig-0.2.4

Description: 用于语音识别语音增强方面的matlab工具包,非常值得参考-for Speech Recognition speech enhancement of Matlab tool kit is very worthwhile reference! !
Platform: | Size: 193536 | Author: 袁坤 | Hits:

[Speech/Voice recognition/combinespeechsdp(speechdspprocessing)

Description: 语音信号的相关知识,语音合成,语音识别语音增强-Voice signals related knowledge, speech synthesis, speech recognition Speech Enhancement
Platform: | Size: 23527424 | Author: 蔡辉迁 | Hits:

[Other11111

Description: 语音信号数字处理是一门涉及面很广的交叉科学,这本书介绍了语音信号的数字表示,矢量量化,隐马尔科夫模型,语音合成,语音识别,语音增强,说话人识别等知识-Speech signal digital processing is a wide-ranging cross-science, this book describes a digital representation of the speech signal, vector quantization, hidden Markov models, speech synthesis, speech recognition, speech enhancement, speaker recognition of such knowledge
Platform: | Size: 23527424 | Author: 张玉 | Hits:

[Othersinemodel

Description: 语音建模直接影响语音识别,语音增强等后续工作,这里语音信号利用正弦模型进行建模,仿真结果良好-Voice Modeling a direct impact on speech recognition, speech enhancement and other follow-up work, where the use of sinusoidal model for speech signal modeling, simulation with good results
Platform: | Size: 3072 | Author: 孙艳 | Hits:

[AI-NN-PRhundun

Description: 这是有关非线性在语音预测编码、识别等方面的应用,还有神经网络方法在语音预测编码、语音增强、识别等方面的应用,相当有用哦!-This is the non-linear prediction in speech coding, recognition and other applications, as well as neural network prediction in speech coding, speech enhancement, recognition and other applications, useful Oh!
Platform: | Size: 3284992 | Author: 高菲悦 | Hits:

[Speech/Voice recognition/combineVariableNoisySpeechEnhancementAlgorithmPerformance

Description: 语音增强是影响语音识别系统性能的重要成分。为了比较语音增强算法的性能,采用Matlab软件进行了数值仿真,对不同噪声环境下的语音用3种不同的方法进行降噪,采用信噪比、端点检测等方法来降噪效果,并对几种增强算法的性能进行了比较分析。结果表明,在变噪声环境下短时谱MMSE法最佳,谱减法和维纳滤波法各有优点。-Speech enhancement of voice recognition is an important component of system performance. In order to compare the performance of speech enhancement algorithm using the Matlab software, a numerical simulation, speech under different noise environments with 3 different methods of noise reduction, the use of signal to noise ratio, endpoint detection method to the noise reduction effect, and a few kinds of enhanced performance of the algorithm were compared. The results show that changing the noise environment in the MMSE method was the best short-term spectrum, spectral subtraction and Wiener filtering methods have their advantages.
Platform: | Size: 376832 | Author: static | Hits:

[Speech/Voice recognition/combineSpeech-enhancement-

Description: 基于matlab仿真的语音增强算法,语音增强是语音识别的预处理,通过语音增强可以很好的进行语言识别-Matlab simulation-based speech enhancement algorithms, speech recognition, speech enhancement is pre-processing, through the speech enhancement for speech recognition can be good
Platform: | Size: 217088 | Author: 张万涛 | Hits:

[matlabmatlabMIDItools

Description: VOICEBOX: Speech Processing Toolbox for MATLAB LPC Analysis of Speech Speech Synthesis Speech Enhancement Speech Recognition-VOICEBOX is a speech processing toolbox consists of MATLAB routines . LPC Analysis of Speech Speech Synthesis Speech Enhancement Speech Recognition
Platform: | Size: 16384 | Author: Rui | Hits:

[Speech/Voice recognition/combinespeech-recognition-speech-enhancement-matlab-toolk

Description: 语音识别语音增强方面的matlab工具包-Aspects of speech recognition, speech enhancement matlab toolkit
Platform: | Size: 181248 | Author: micron | Hits:

[Otherspeech-signal-processing--by-ZhaoLi

Description: 语音信号处理__赵力。共分十二章,内容包括:绪论、语音信号处理的基础知识、语音信号的分析技术、语音信号的矢量量化、隐马尔可夫模型技术、神经网络在语音信号处理中的应用、语音编码、语音合成、语音识别、说话人识别和语种辨识技术、语音信号的情感信息处理技术、语音增强技术-Voice signal processing __ Zhao. Divided into 12 chapters, including: the introduction, the basics of voice signal processing, speech signal analysis techniques, the speech signal vector quantization and hidden Markov model, neural network applications in speech signal processing, speech coding, speech synthesis, speech recognition, speaker recognition and language identification technology, the voice signal emotional information processing technology, speech enhancement technology
Platform: | Size: 9973760 | Author: luocw138 | Hits:

[OtherDigital-Voice-Processing-

Description: 本书系统地阐述了语音信号处理的原理、方法、技术和应用,同时给出了部分内容对应的MATLAB仿真源程序。全书共12章,第1章至第7章是基本理论部分,包括语音信号的数字模型、语音信号的短时时域分析和频域分析、语音信号的同态处理、语音信号线性预测分析和矢量量化;第8章至第12章是应用部分,包括语音编码、语音合成、语音识别、语音增强和语音处理的实时实现。本书内容全面,重点突出,原理阐述深入浅出,注重理论与实际应用的结合,可读性强。-This book describes the speech signal processing principles, methods, techniques and applications, and gives the corresponding part of the contents of the MATLAB simulation source. The book is 12 chapters, Chapter 1 to Chapter 7 is the basic theoretical part, including voice signal digital model, speech signal analysis in time domain and frequency domain analysis, speech signal homomorphic processing, speech signal analysis and linear prediction vector quantified Chapter 8 to Chapter 12 is the application of parts, including speech coding, speech synthesis, speech recognition, speech enhancement and voice processing, real-time implementation. The book is comprehensive, focused and Rationale layman, focusing on the combination of theory and practical application, readable.
Platform: | Size: 15129600 | Author: Qin | Hits:

[Graph Recognizefinger

Description: 图像识别利用MATLAB或VC编写一个系统,使得该系统能满足信息处理、频域处理、语音增强、识别等内容。-Image recognition using MATLAB or VC write a system so that the system can meet the information processing, frequency domain processing, speech enhancement, recognition and so on.
Platform: | Size: 2048 | Author: 王刚 | Hits:

[matlabslides

Description: Input method and Recognition limitation: Recognizes what you say, not what you mean, Not artificial intelligence, Only as good as the application, Speech recognition means recognizing specific words and voice recognition means recognizing a specific voice i.e. what was said versus who said it.
Platform: | Size: 504832 | Author: nutan | Hits:

[Speech/Voice recognition/combineSpeech Encoding - Frequency Analysis MATLAB

Description: The speech signal for the particular isolated word can be viewed as the one generated using the sequential generating probabilistic model known as hidden Markov model (HMM). Consider there are n states in the HMM. The particular isolated speech signal is divided into finite number of frames. Every frame of the speech signal is assumed to be generated from any one of the n states. Each state is modeled as the multivariate Gaussian density function with the specified mean vector and the covariance matrix. Let the speech segment for the particular isolated word is represented as vector S. The vector S is divided into finite number of frames (say M). The i th frame is represented as Si . Every frame is generated by any of the n states with the specified probability computed using the corresponding multivariate Gaussian density model.
Platform: | Size: 787456 | Author: Khan17 | Hits:
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