Search - algorithm of speech recognition

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[Software Engineering] EM DL : 0: 期望极大化（EM）算法及其应用，对从事统计研究的人比较游泳。-Expectation maximization (EM) algorithm and its application, to the conduct of statistical research compared to swimming.
Date : 2026-01-01 Size : 91kb User : 胡兵
[Software Engineering] the-application-and-research-based-on-dsp-speech-p DL : 0: 本文针对语音识别处理系统中面临的主要问题和关键点，利用语音处理系统对语音处理的一些关键点进行讨论研究。并且利用一些基本算法对语音处理的部分参数进行实验。 -In this paper, speech recognition systems deal with major issues and key points, use of voice processing systems to handle voice some of the key points in my research. And use some of the basic algorithm to deal with part of speech parameters of the experiment.
Date : 2026-01-01 Size : 2.84mb User : xcs
[Software Engineering] Desktop DL : 0: This project gives the design of control system and speaker recognition code using matlab. Matlab’s straightforward programming interface makes it an ideal tool for speech analysis projects. For the current project, experience was gained in general matlab programming and the design of control system. A basic speaker recognition algorithm has been written to sort through a rule base in matlab and choose the one most likely match based on the pre define time frame of the speech utterance.
Date : 2026-01-01 Size : 183kb User : pingu
[Software Engineering] Speech-recognition-in-MATLAB- DL : 0: 介绍了一种基于MATLAB的多个特定人连接词语音识别的方法，并提出了在进行端点检测时，引入平均的概念能进一步提高识别率。此设计是以LPCC系数、DTW算法为核心的基于图形界面的设计。-A Based on MATLAB more specific conjunctions speech recognition, and during endpoint detection, the introduction of the concept of average to further improve the recognition rate. This design is based on LPCC coefficients, the DTW algorithm as the core-based graphical interface design.
Date : 2026-01-01 Size : 357kb User : lhj
[Software Engineering] PCA DL : 0: 针对稀疏表示识别方法需要大量样本训练过完备字典且特征冗余度较高的问题，提出了结合过完备字典学习与PCA降维的小样本语音情感识别算法.该方法首先用PCA降维方法将特征降维，再将处理后的特征用于过完备字典训练与稀疏表示识别方法，从而给出了语音情感特征的稀疏表示方法，并确定了新算法的具体步骤.为验证其有效性，在同等特征维数下，将方法与BP, SVM进行比较，并对比、分析语音情感特征稀疏化前后对语音情感识别率、时间效率以及空间效率的影响.试验结果表明，所提出方法的识别率比SVM与BP高与采用稀疏化前的特征相比，稀疏化后的特征向量更便于处理，平均识别率提高约15 ，时间效率提高近原来的1 /2，空间效率提升近原来的1 /3. -Identification methods for sparse representation requires a lot of training samples and high over-complete dictionary feature redundancy problem, a combination of over-complete dictionary learning and PCA dimension small sample speech emotion recognition algorithms. Firstly, the PCA dimension reduction methods feature reduction, feature and then treatment for the over-complete dictionary training and recognition sparse representation, which gives a speech emotion feature sparse representation, and to determine the specific steps of the new algorithm. To verify its validity, in Under the same number of features, the method and BP, SVM compare and contrast, analyze the impact before and after the speech emotion feature sparse speech emotion recognition rate, time-efficient and space-efficient. experimental results show that the recognition rate of the proposed method than High SVM and BP compared to pre-thinning characteristics using eigenvectors easier after thinning processing, the av
Date : 2026-01-01 Size : 615kb User : wangming
[Software Engineering] viterbi DL : 0: 语音识别HMM算法中的解码功能的程序，其中是根据观测序列和已知模型去求状态序列-Speech recognition HMM algorithm decoding process, which is to seek observer status in accordance with the sequence and the known sequence of the model
Date : 2026-01-01 Size : 1kb User : 张宇
[Software Engineering] Voice_Recognition_System_in_Noisy_Environment DL : 0: voice recognition in noisy environment Human life could be much more comfortable, if global machinery works on voice commands. There are lot of products available in the market those provide us automated voice controlled working experience. Voice-identification is a kind of technology in which, machine responds to human voice. The goal of this project is to design and implement voice controlled embedded system in noisy environment. The project consists software and hardware design. The software part is to eliminate noise the original signal and develop the speech recognition algorithm (DTW). The hardware is used for speech recognition.-voice recognition in noisy environment Human life could be much more comfortable, if global machinery works on voice commands. There are lot of products available in the market those provide us automated voice controlled working experience. Voice-identification is a kind of technology in which, machine responds to human voice. The goal of this project is to design and implement voice controlled embedded system in noisy environment. The project consists software and hardware design. The software part is to eliminate noise the original signal and develop the speech recognition algorithm (DTW). The hardware is used for speech recognition.
Date : 2026-01-01 Size : 1.03mb User : suraj kumar
[Software Engineering] dtw DL : 0: dtw动态时间规划算法，应用于语音识别，语音处理，说话人识别的应用中。-DTW dynamic programming algorithm, used in speech recognition, speech processing, application of speaker recognition.
Date : 2026-01-01 Size : 6kb User : 裴孟菲
[Software Engineering] 20P_ISOLATED DL : 0: This paper describes an approach of isolated speech recognition by using the Mel-Scale Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW). Several features are extracted speech signal of spoken words. An experimental of total five speakers, speaking 10 digits each is collected under acoustically controlled room is taken. MFCC are extracted speech signal of spoken words. To cope with different speaking speeds in speech recognition Dynamic Time Warping (DTW) is used. DTW is an algorithm, which is used for measuring similarity between two sequences, which may vary in time or speed.-This paper describes an approach of isolated speech recognition by using the Mel-Scale Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW). Several features are extracted speech signal of spoken words. An experimental of total five speakers, speaking 10 digits each is collected under acoustically controlled room is taken. MFCC are extracted speech signal of spoken words. To cope with different speaking speeds in speech recognition Dynamic Time Warping (DTW) is used. DTW is an algorithm, which is used for measuring similarity between two sequences, which may vary in time or speed.
Date : 2026-01-01 Size : 652kb User : ali khaleel
[Software Engineering] DTWword DL : 0: DTW算法用于语音识别的资料介绍，不错的参考资料。-DTW algorithm for speech recognition of information, a good reference.
Date : 2026-01-01 Size : 20kb User : 刘伟