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planevoice1
- 航空噪声背景下的语音端点检测和语音增强算法，在信噪比很低的强航空噪声背景下，效果特别好-aviation noise background voice endpoint detection and voice enhancement algorithms, and very low signal to noise ratio in the strong aviation background noise, particularly effective
sphinxbase-0.1.tar
- sphinxbase是卡内基梅隆大学著名的sphinx语音识别工程的公用库，里面实现了语音的AD处理，端点检测，去噪等功能。-sphinxbase Carnegie Mellon University is famous sphinx voice recognition works in the common the inside of the voice of the AD, endpoint detection, denoising function.
xiaoboyuyinduandianjianxe
- 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
基于LPC美尔倒谱特征的带噪语音端点检测
- 基于LPC美尔倒谱特征的带噪语音端点检测.rar格式为ｖｉｐ-America Fall Cepstral Noisy voice endpoint detection. Rar format vip
基于倒谱特征的带噪语音端点检测
- 基于倒谱特征的带噪语音端点检测.rar格式为ｖｉｐ-based Cepstral Noisy voice endpoint detection. Rar format vip
航空噪声背景下的语音端点检测和语音增强算法
- 航空噪声背景下的语音端点检测和语音增强算法，在信噪比很低的强航空噪声背景下，效果特别好
语音端点检测Matlab程序
- 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
ASKBPSk
- 噪声背景下的语音端点检测和语音增强算法，在信噪比很低的强航空噪声背景下，-aviation noise background voice endpoint detection and voice enhancement algorithms, and very low signal to noise ratio in the strong aviation background noise, particularly effective
vad
- 几篇带噪声语音信号端点检测算法的论文，希望对大家有用-Speech signal with noise several endpoint detection algorithm for papers, in the hope that useful
VoiceActivityDetection
- 在本文中,主要讲了在语音识别和语音合成之前我们所要做的主要工作，包括去噪,预加重,端点检测,特征参数提取等技术.-In this article, the main speaker in the speech recognition and speech synthesis to be done before we have major work, including de-noising, pre-emphasis, endpoint detection, feature extraction
voice
- 基于谱减法的语音端点检测，运用了语音增强，去噪，谱减，加窗，端点检测等方法-Spectral subtraction based speech endpoint detection, using a speech enhancement, denoising, minus spectrum, add windows, endpoint detection methods such as
speech
- 本文首先总结了现有典型的语音端点检测算法，分析了其中几种 端点检测算法所选用的特征，给出了仿真结果和一些改进。随后提出 了噪声环境下两种语音端点检测新算法。算法一:从基于人耳的听觉 系统出发，对Mel标度滤波器组进行研究，提出了语音信号的一种新 的自适应时频参数，该参数既考虑了声道响应，又符合人耳听觉特性， 仿真结果表明了它的优越性。算法二:结合抗噪性能好的Mel倒谱距 离和多带能量嫡特征提出了一种改进的孤立词端点检测算法，该算法 不需要估计背景噪声来调整门限闽值，仿
endpoint_detection_with_noise
- 提出了一种基于时频方差和的语音端点检测算法。实验证明该算法能够在低信噪比的情况下,准确地检测出语音信号-Proposed based on time-frequency variance and Speech Endpoint Detection Algorithm. Experiments show that the algorithm at low SNR cases, accurately detect the speech signal
sang
- 一种基于信息熵的Matlab端点检测算法，抗噪性能比较好-Matlab based on information entropy of the endpoint detection algorithm, better anti-noise performance
voice_prcossing
- 语音增强，倒谱，端点检测，共振峰检测，去噪-Speech enhancement, cepstrum, endpoint detection, formant detection, denoising
Endpoindetectionspectralenhancement
- 基于端点检测的谱减法语音增强，语音的去噪算法仿真程序，可以进一步改进-Endpoint detection of the spectral subtraction based speech enhancement
11
- 为提高语音端点检测系统在低信噪(0 dB 以下) 下 检测的准确率, 提出了一种基于谱熵的端点检测算法。将每 帧信号分为16 个子带, 选取频谱分布在250～ 3. 5 kHz 并且 能量不超过该帧总能量90 的子带, 计算经过语音增强后的 子带能量以及各子带信噪比, 根据各子带信噪比的不同调整 其在整个谱熵计算过程中的权重, 然后平滑谱熵, 以最终的 谱熵作为端点检测的依据-To improve endpoint detection system in the low
audio_1
- 语言去噪端点检测 进行语言去噪和端点检测-Language de-noising endpoint detection
double_threshold
- 传统的语音信号双门限端点检测算法，适用于高信噪比，低信噪比不适用。(The traditional double threshold detection algorithm for speech signal is suitable for high signal to noise ratio and low signal to noise ratio.)
matlab
- 这是一个具有语音的采集、读取、内插恢复、重采样，语音的时域参数的计算、端点的检测、基音周期的提取，语音的加噪、滤波及每次处理后语音的播放等功能的语音信号处理系统。(speech signal processing)