Search - speech analysis matlab

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[Software Engineering] 111 DL : 0: 录制一段个人的语音信号，并对录制的信号进行采样；画出采样后语音信号的时域波形和频谱图；给定滤波器的性能指标，采用双线性变换法和窗函数法设计滤波器，并画出滤波器的频率响应；然后用自己设计的滤波器对采集的信号进行滤波，画出滤波后信号的时域波形和频谱，并对滤波前后的信号进行对比，分析信号的变化；回放语音信号；最后，设计一个信号处理系统界面。-Record a personal voice signal, and recording the signal is sampled draw sampled speech signal time-domain waveform and frequency spectrum for a given filter performance, the bilinear transformation and design of filter window functions and draw the frequency response filter then filter of their own design collection of the signal filtering, to draw the filtered signal in time domain waveforms and frequency spectrum, and filtering the signal before and after comparison, analysis of signal changes playback audio signals Finally, a signal processing system interface design.
Date : 2026-01-01 Size : 6kb User : liudan
[Software Engineering] lunwen DL : 0: 本文简要介绍了语音信号采集与分析的发展史以及语音信号的特征、采集与分析方法，并通过PC机录制自己的一段声音，运用Matlab进行仿真分析，最后加入噪声进行滤波处理，比较滤波前后的变化。-This paper introduces the voice signal acquisition and analysis of the history and characteristics of speech signals, sampling and analysis methods, and through a PC, record your own voice, use of Matlab simulation and analysis, and finally adding noise filtering, comparing before and after filtering change.
Date : 2026-01-01 Size : 192kb User : Conan King
[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] New-Folder-(4) DL : 0: In this paper the analysis of the compression process was performed by comparing the compressed signal against the original signal. To do this the most powerful speech analysis and compression techniques such as Linear Predictive Coding (LPC) and Discrete Wavelet Transform (DWT) was implemented using MATLAB. Here nine samples of spoken words are collected from different speakers and are used for implementation. The results obtained from LPC were compared with other compression technique called Discrete Wavelet Transform. Finally the results were evaluated in terms of compressed ratio (CR), Peak signal-to-noise ratio (PSNR) and Normalized root-mean square error (NRMSE).The result shows that DWT performance was better for these samples than the LPC method.
Date : 2026-01-01 Size : 144kb User : Ambika
[Software Engineering] lpc DL : 0: This MATLAB exercise computes the log magnitude of the STFT of a specified frame of speech. Then, using the same frame of speech, the exercise computes LPC log spectral matches to the speech frame, using the autocorrelation method, the covariance method, and the lattice method. The four resulting log magnitude responses ( the STFT of the speech frame and the three LPC analysis methods) are then plotted on a common plot, and compared in terms of how each LPC analysis method approximates the STFT log magnitude response. -This MATLAB exercise computes the log magnitude of the STFT of a specified frame of speech. Then, using the same frame of speech, the exercise computes LPC log spectral matches to the speech frame, using the autocorrelation method, the covariance method, and the lattice method. The four resulting log magnitude responses ( the STFT of the speech frame and the three LPC analysis methods) are then plotted on a common plot, and compared in terms of how each LPC analysis method approximates the STFT log magnitude response.
Date : 2026-01-01 Size : 2.58mb User : burak
[Software Engineering] formant_estimation DL : 0: his MATLAB exercises illustrates an algorithm for estimating the locations of the formants of voiced speech intervals based on the locations of the speech polynomial roots as obtained a frame-based analysis of a speech signal using the method of Linear Prediction Analysis. A key aspect f this algorithm is finding regions of quasi-contiguous speech frames (where the first three formants form a contiguous region over the duration of the voiced region), and then extending these regions (both backward and forward) based on a somewhat weaker criterion for contiguous behavior of the formants. The file 4.7 Formant Estimation.pdf provides a User s Guide for this exercise.-his MATLAB exercises illustrates an algorithm for estimating the locations of the formants of voiced speech intervals based on the locations of the speech polynomial roots as obtained a frame-based analysis of a speech signal using the method of Linear Prediction Analysis. A key aspect f this algorithm is finding regions of quasi-contiguous speech frames (where the first three formants form a contiguous region over the duration of the voiced region), and then extending these regions (both backward and forward) based on a somewhat weaker criterion for contiguous behavior of the formants. The file 4.7 Formant Estimation.pdf provides a User s Guide for this exercise.
Date : 2026-01-01 Size : 2.7mb User : BIN TENG
[Software Engineering] tingmang-V5.1 DL : 0: matlab编写的元胞自动机，基于欧几里得距离的聚类分析，完整的基于HMM的语音识别系统。- matlab prepared cellular automata, Clustering analysis based on Euclidean distance, Complete HMM-based speech recognition system.
Date : 2026-01-01 Size : 5kb User : 胥财
[Software Engineering] wgfkr DL : 0: FIR 底通和带通滤波器和IIR 底通和带通滤波器，matlab小波分析程序，完整的基于HMM的语音识别系统。- Bottom-pass and band-pass FIR and IIR filter bottom pass and band-pass filter, matlab wavelet analysis program, Complete HMM-based speech recognition system.
Date : 2026-01-01 Size : 5kb User : 吴康卫