Description: 语音端点检测是语音识别中至关重要的技术。无论军用还是民用，语音端点检测都有着广泛的应用。在低信噪比的环境中进行精确的端点检测比较困难，尤其是在无声段或者发音前后-voice activity detection is critical speech recognition technologies. Whether military or civilian, voice endpoint detection have broad application. Low signal-to-noise ratio in the environment for accurate endpoint detection more difficult, especially in or pronunciation of the silent before and after Platform: |
Size: 531719 |
Author:李一 |
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Description: 语音端点检测是语音识别中至关重要的技术。无论军用还是民用，语音端点检测都有着广泛的应用。在低信噪比的环境中进行精确的端点检测比较困难，尤其是在无声段或者发音前后-voice activity detection is critical speech recognition technologies. Whether military or civilian, voice endpoint detection have broad application. Low signal-to-noise ratio in the environment for accurate endpoint detection more difficult, especially in or pronunciation of the silent before and after Platform: |
Size: 531456 |
Author:李一 |
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Description: ITU-T G.729语音压缩算法。
description:
Fixed-point description of commendation G.729 with ANNEX B Coding of Speech at 8 kbit/s using Conjugate-Structure Algebraic-Code-Excited Linear-Prediction (CS-ACELP) with Voice Activity Decision(VAD), Discontinuous Transmission(DTX), and Comfort Noise Generation(CNG).-ITU-T G.729 voice compression algorithms. description: Fixed-point description of commendation G.729 with ANNEX B Coding of Speech at 8 kbit/s using Conjugate-Structure Algebraic-Code-Excited Linear-Prediction (CS-ACELP) with Voice Activity Decision (VAD), Discontinuous Transmission ( DTX), and Comfort Noise Generation (CNG). Platform: |
Size: 111616 |
Author:kevin |
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Description: 在低信噪比条件下的语音端点检测与增强方法-In low signal to noise ratio under the conditions of voice activity detection and enhancement method Platform: |
Size: 294912 |
Author:wangkaixi |
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Description: 在有背境噪音的条件下，进行语音端点检测，并取得很好的效果-Have background in the noise conditions, for voice activity detection and achieved good results Platform: |
Size: 622592 |
Author:读宴宾 |
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Description: 为了实现高速语音特征参数的提取，在分析了美尔频率倒谱特征参数提取算法的基础上，提出了算法的硬件
设计方案，介绍了各模块的设计原理。该方案增加了语音激活检测功能，可对语音信号中的噪音帧进行检测，提高了特征参
数的可靠性。-In order to achieve high-speed voice characteristic parameter extraction, in the analysis of Mel frequency cepstral feature extraction algorithm is proposed based on the algorithm the hardware
Design, describes the design principles of each module. The program increased the Voice Activity Detection feature, which allows voice signals to detect the noise frame to improve the characteristic parameters
The number of reliability. Platform: |
Size: 749568 |
Author:于高 |
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Description: In this paper we propose a method for voice
activity detection (VAD) in a speech signal recorded in the
presence of noise. The so-called endpoint detection (EPD),
i.e., detection of voice activity (speech) boundaries is very
difficult if the signal is acquired in noisy environments. The
proposed VAD method uses an additional stage of wavelet
subband denoising. We compared this approach with other
standard methods i.e.: zero-crossing rate and spectral
entropy analysis. Additionally we present in this paper our
basic results illustrating the main aim of this contribution,
consisting in application of intelligent denoising strategies
to various VAD algorithms. Platform: |
Size: 276480 |
Author:Tomasz |
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Description: 语音端点检测Matlab程序，附带计算信噪比的Matlab子程序，文本文档内是常用语音库的下载网址，非常使用-Voice activity detection Matlab program calculated signal to noise ratio with Matlab subroutine, the text is a common voice within the document library to download URL is used Platform: |
Size: 41984 |
Author:Chris |
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Description: 为提高语音端点检测(VAD)在较低信噪比(10 dB)下的准确率,提出一种基于短时分形维数的改进算法。结合语音信号的特点,对2种常用的语音信号分形维数计算方法进行了比较和选择,同时采用动态跟随门限值实现语音端点的自适应检测。试验结果表明:对于信噪比6~10 dB的带噪语音,此方法可以实现整段语音的检测,而且具有一定的噪声鲁棒性,系统运行期间能够自适应调整门限值以适应环境噪声的变化,提高了VAD算法的准确率。这个是源码matlab。-In order to improve voice activity detection (VAD) in low SNR (10 dB) accuracy under proposed based on short-time fractal dimension of the improved algorithm. Combined with the characteristics of the speech signal, to 2 commonly used fractal dimension of speech signals are compared and calculated choice to follow the same dynamic endpoint threshold adaptive detection of voice. The results showed that: 6 ~ 10 dB for the signal to noise ratio of noisy speech, this method can detect the entire speech, but has some noise robustness, the system can be adaptively adjusted during operation to adapt to environmental noise threshold of changes to improve the accuracy of VAD algorithms. This is the source matlab. Platform: |
Size: 79872 |
Author:liuhongfu |
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Description: detect voice from signal of speach Voice Activity Detector (VAD)
with MMSE a posteriori noise estimation and Decision-Directed SNR estimation-detect voice from signal of speach Voice Activity Detector (VAD)
with MMSE a posteriori noise estimation and Decision-Directed SNR estimation Platform: |
Size: 2048 |
Author:blackgk |
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Description: An Automatic Gain Controller (AGC) for speech signals embedded in additive noise requires Voice Activity
Detection (VAD) to avoid noise amplification, a peak level detector for computing gain, and a gain
controller for adjusting gain. This paper describes a low computational-intensive software AGC for use in
handheld devices. The AGC provides options for static and dynamic noise floor estimation in a VAD
module. Further, this paper describes analog and digital gain adjustment with gain curve selection to allow
for distance perception during the AGC operation.
Platform: |
Size: 724992 |
Author:azza |
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Description: vad（语音活动检测）的matlaab代码，使用频域的方法计算信噪比。
-vad (voice activity detection) matlaab code, using the frequency domain method to calculate the signal to noise ratio. Platform: |
Size: 1024 |
Author:mmzz3211 |
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Search - voice activity noise