OLA

一种改进的DTW语音识别算法,可以加快识别速度.(An improved DTW speech recognition algorithm, can accelerate the recognition speed.)

FastICA算法，用于信号的独立分量分析，在ICA的基础上加快了收敛速度，有更高的效率！并且增加了图象界面，使用方便！(FastICA algorithm, the signal for an independent component analysis, at the ICA on the basis of accelerating the convergence rate, a more efficient! And to increase the image user interface!)

本文主要研究普通计算环境下语音自动识别(ASR)技术的软件实时实现，基于语音识别的基本原理和过程。在VC环境下建立了一套语音识别系统及其演示软件。实验表明，该系统对特定人情况有较高的识别率和一定的实时性(In this paper, under the computing environment on general automatic speech recognition (ASR) technology to achieve real-time software, speech recognition based on the basic principles and processes. VC environment in the establishment of a voice recognition system and its presentation software. The experiments show that the systems are in particular have a high recognition rate and a certain degree of real-time)

　提出了一种新的连续型隐马尔可夫模型(HMM ) 的概率密度函数, 并导出了一系列的参 数寻优迭代公式,(A new Continuous Hidden Markov Model (HMM) of the probability density function, and derived a series of parameters optimization iteration formula,)

实现mffc求解 并且可利用hmm进行孤立词识别(Solving mffc realize and can be used for isolated word recognition hmm)

一个完整的语音端点检测MATLAB程序序，包含有完整的文件，通过调试，正确可用 (An integrated voice activity detection MATLAB program, includinng complete documentation, through testing, can be used correctly )

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.)

基于LMS算法和NLMS算法的自适应声回波消除器AEC，实现的主要功能是：在用户对电视发出的指令混杂了电视扬声器的声学回声的情况下，滤掉电视声音得到较为纯净的用户语音指令信号。(The main function of the adaptive filter based on the LMS algorithm and the NLMS algorithm is mixed: in the instruction issued by the user on the television TV speakers acoustic echo case, the TV sound was removed by filtration to obtain relatively pure user voice command signal.)

语音信号处理c语言程序-音高、加窗、MFCC、PLP、等(C programming language speech signal processing- pitch, add window, MFCC, PLP, etc)

一种加权K近邻语音情感识别程序，包括部分柏林语音情感库(A Weighting K-nearest neighbor speech emotion recognition program, including some libraries Berlin Speech Emotion)