Search - VAD

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【MiddleWare】 word_recognition DL : 0: word recognition using VAD MFCC G-word recognition using VAD MFCC GMM
Update : 2024-05-14 Size : 36864 Publisher : sagy
【matlab】 vad_directed_by_noise_classification DL : 0: vad_directed_by_noise_classification.m This code is an implementation of VAD algorithm proposed in: Robust voice activity detection directed by noise classification please cite the article in your paper: Robust voice activity detection directed by noise classification, J Saeedi, SM Ahadi, K Faez Signal, Image and Video Processing, 1-12 the folder is also contained the following * different noise models for svm * different sub_functions. * three speech signal TIMIT dataset and their vad labels Note that you need to download noise dataset from http://spib.rice.edu/spib/select. and libsvm toolbox from http://www.csie.ntu.edu.tw/~cjlin/libsvm/ It should be mentioned that both speech and noise should be sampled at 8 KHz. Jamal Saeedi Amirkabir University of Technology Electrical Engineering Department-vad_directed_by_noise_classification.m This code is an implementation of VAD algorithm proposed in: Robust voice activity detection directed by noise classification please cite the article in your paper: Robust voice activity detection directed by noise classification, J Saeedi, SM Ahadi, K Faez Signal, Image and Video Processing, 1-12 the folder is also contained the following * different noise models for svm * different sub_functions. * three speech signal TIMIT dataset and their vad labels Note that you need to download noise dataset from http://spib.rice.edu/spib/select. and libsvm toolbox from http://www.csie.ntu.edu.tw/~cjlin/libsvm/ It should be mentioned that both speech and noise should be sampled at 8 KHz. Jamal Saeedi Amirkabir University of Technology Electrical Engineering Department
Update : 2024-05-14 Size : 1024 Publisher : Ilya
【matlab】 frequency-band-variance-of-VAD DL : 0: 语音和噪声在频谱域中的特性差异较大，基于此给出频带方差的端点检测程序。-Speech and noise have differences in the spectral domain feature, based on the given frequency band variance program applied in the speech endpoint detection.
Update : 2024-05-14 Size : 1024 Publisher : 黄燕
【matlab】 Autocorrelation-Function-for-VAD DL : 0: 基于自相关函数最大值的语音端点检测算法,即使在较低信噪比情况下采用该算法仍能较准确地检测出语音信号的端点位置。-The maximum of autocorrelation function of sonant and sonata′s autocorrelation function characteristics after autocorrelation function filtered through a lowpass are studied，this method can detect the voice endpoint exactly even in a low SNR environment.
Update : 2024-05-14 Size : 1024 Publisher : 黄燕
【matlab】 Main-peak-ratio-for-VAD DL : 0: 噪声帧与有话帧之间主副峰的比值有差距，利用该特性提取端点。-The main peak ratio of noise and words frame has a gap,by using the feature extraction endpoint.
Update : 2024-05-14 Size : 1024 Publisher : 黄燕
【matlab】 Auto-Correlated-Cosine-for-VAD DL : 0: 在基于高维空间和自相关函数的基础上,基于短时自相关夹角余弦值的语音端点检测。-On the basis of higher dimension space and auto-corre lated func tions, this paper presents a new method of end point detection of speech, a c ross zero speech recognition method based on short time auto-correlated corner cosine.
Update : 2024-05-14 Size : 1024 Publisher : 黄燕
【matlab】 wavelet-packet-BARK-for-VAD DL : 0: 小波包分解构成BARK子带，利用子带进行语音端点检测。-Wavelet packet decomposition constitutes a BARK subband, the use of subband for speech endpoint detection.
Update : 2024-05-14 Size : 1024 Publisher : 黄燕
【matlab】 log--spectral-distance-for-VAD DL : 0: 语音增强之前先进行端点检测，对有话帧和噪声帧作不同处理，利用对数频谱距离进行端点检测。-Speech enhancement for endpoint detection, before to have words for different frame and noise frame processing, using logarithmic spectrum distance for endpoint detection.
Update : 2024-05-14 Size : 1024 Publisher : 黄燕
【Linux-Unix】 vad_core DL : 0: This header file includes the descriptions of the core VAD calls.
Update : 2024-05-14 Size : 6144 Publisher : wwsogei
【DSP program】 ssubmmsev DL : 0: performs speech enhancement using the MMSE or log MMSE criteria with VAD-based noise estimate
Update : 2024-05-14 Size : 6144 Publisher : Jatin Koshiya
【Audio program】 webrtc_deps.tar DL : 0: webrtc基础音频信号处理，以及CNG模块提取，并向其中附加了G7221C编解码器，用于处理7221音频数据和VAD活动语音检测后的CNG包，用于服务器处理流媒体数据，混音等的操作。-webrtc base audio signal processing, as well as CNG module extracts, to which is added G7221C codec 7221 for processing audio data and voice activity detection VAD CNG after package for the server to process streaming data, mixing and other operations .
Update : 2024-05-14 Size : 396288 Publisher : 徐伟
【matlab】 VQVAD DL : 0: Vector Quantization and VAD application
Update : 2024-05-14 Size : 7168 Publisher : Mateus
【Software Engineering】 Adaptive-Linear-Energy-Based-Detector DL : 0: An approach to detect voice. (VAD)
Update : 2024-05-14 Size : 497664 Publisher : pipi
【Software Engineering】 Overview-VAD DL : 0: overview all approach to detect voice
Update : 2024-05-14 Size : 379904 Publisher : pipi
【Internet-Network】 webrtc_vad DL : 0: WebRTC中提取出来的vad检测代码，目前读取全部为1。希望各位高手能够修正。-WEBrtc vad dection，now has a problem,read all data is 1,hope others can resolve it.
Update : 2024-05-14 Size : 601088 Publisher : LJ
【matlab】 vad1 DL : 0: 双门限的VAD代码，可用。带有实验语音数据。-Double threshold of VAD code available. Experiment with voice data.
Update : 2024-05-14 Size : 1146880 Publisher : 六颗
【DataMining】 vad DL : 0: 双门限端点检测。因为低噪声导致假过零率的产生，进行了算法改进。可以直接调用函数运行，亲测-Dual threshold endpoint detection. Because of the low noise cause false over-produce zero rate, the algorithm was improved. It can directly call the function run, pro-test
Update : 2024-05-14 Size : 2048 Publisher : chenwenqiang
【matlab】 vad DL : 1: 关于端点检测的几种方法，语音样本是自己录制的，对传统算法做了一些改进，加入了去噪，去噪之后再进行端点检测，均调通 vad0303：自己设置调整门限为一定值 vad0310：根据能量值和过零率设置门限，自适应门限值 vad0310_2：基于比例因子的门限自调整 vad0310.m加入了噪声，端点检测前都噪声进行了处理 entropy.m：基于自适应子带频谱熵的稳健性语音端点检测可用于语音增强及端点检测 dbdoor.m：双门限算法，用于语音端点检测。可以通过调整门限值，并加入门限自适应算法，实现语音端点检测-Several methods on endpoint detection, recording their own voice samples, the traditional algorithm has made some improvements, adding a de-noising, and then after de-noising endpoint detection are transferred through
Update : 2024-05-14 Size : 2134016 Publisher : 王冲
【Speech/Voice recognition/combine】 vad DL : 0: liunx环境下的语音端点检测程序，使用alsa声卡进行读取数据，最长支持四秒的语音片段-liunx environment voice endpoint detection procedures
Update : 2024-05-14 Size : 9216 Publisher : Phan Lee
【Embeded-SCM Develop】 STM32-Speech-Recognition-Master DL : 0: 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 上存储空间相对较小、计算能力也相对较弱的实际情况，对算法进行优化。最终完成于 STM32 微处理器上的特定人语音识别系统。-Implement speech recognition processing project in commercially available STM32 development board. Identification is the process: pre-filter, ADC, framing, endpoint detection, pre-emphasis, windowing, feature extraction, feature matching. Endpoint detection (VAD) short-time amplitude and short-term zero rate combined. After detecting an effective voice, according to the characteristics of human auditory perception, calculated for each frame of speech Mel Frequency Cepstral Coefficients (MFCC). Then dynamic time warping (DTW) algorithm and feature template matches the final output recognition result. First with Matlab simulation algorithm described above, after several trials to get the optimal value of each coefficient within the desired algorithm. The algorithm will migrate to STM32 development board, the porting process according to the STM32 relatively small storage space, computing power is relatively weak situation of the optimization algorithm. Finally completed on the STM32 micr
Update : 2024-05-14 Size : 325632 Publisher : Chenkly

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