助手标题  
全文文献 工具书 数字 学术定义 翻译助手 学术趋势 更多
查询帮助
意见反馈
   语音活动 的翻译结果: 查询用时:0.017秒
图标索引 在分类学科中查询
所有学科
电信技术
更多类别查询

图标索引 历史查询
 

语音活动
相关语句
  voice activity
     The Research on the Voice Activity Detection in the Environment with High Noise
     高噪声环境下语音活动检测技术的研究
短句来源
     theimplementation of RTP at Windows circumstances voice activity detector (VAD)voice continuity voice compression ,IP Multicast over Windows,and so on0 These areall the problems of transmiting voice over IP network,they affect directly the qualifyof voice.
     这些问题包括IP网络的传输问题、Windows环境下RTP协议的实现、语音活动检测(VAD)、语音抖动、语音压缩及Windows环境下IP多播等问题。
短句来源
     The detection of the presence of speech embedded in various types of non-speech events and background noise is called endpoint detection, speech detection or voice activity detection(VAD).
     语音识别系统的处理对象是有效语音信号,即排除了纯噪声段的语音信号段,这就需要事先从输入信号中找到语音部分的起止点,确定有效语音段的边界,端点检测的目的就是从包含语音的一段信号中确定出语音的起点以及终点,又称语音活动检测(VAD,Voice Activity Detection)。
短句来源
     Time Delay Estimation (TDE) and Voice Activity Detection (VAD) are two key parts in most kinds of array speech enhancement methods and their performance directly affect the results of speech enhancement.
     因此,本文主要研究基于麦克风阵列的语音增强方法。 时延估计和语音活动检测(Voice Activity Detection,简称VAD)技术是阵列增强的重要组成部分,其准确性直接影响到语音增强效果。
短句来源
     Improved Voice Activity Detector Based on the Wavelet Transform
     改进的基于小波变换的语音活动检测算法
短句来源
更多       
  “语音活动”译为未确定词的双语例句
     Voice detection technology (VDT) in a background of high noise
     高噪声环境下的语音活动检测技术
短句来源
     Study of Speech Activity Detective Algorithm Based on LPC Predictive Residual of Speech High Order Statistics
     基于LPC高阶统计量语音活动检测算法的设计与实现
短句来源
     The system stability reached 100% and 98% respectively in high noise background of 100-110dB and 110-115dB. The system ability on anti-jamming was improved and a precision detection of VD was implemented in a high noise background or to unstable noise signals by the developed algorithm.
     在100~110、110~115dB的背景噪声环境,系统稳定性分别为100%和98%。 采用此种算法,增强了系统的抗干扰能力,在高噪声和噪声不太稳定的环境下,实现了对语音活动的精确检测。
短句来源
     These applications can be summarized into two main groups: sound source localization and speech enhancement based on microphone array.
     传声器阵列语音增强作为传声器阵列技术的重要应用之一,涉及时延估计、语音活动检测和语音增强方法三项关键技术。 本文重点研究了这三项关键技术,主要工作如下:
短句来源
     In the reverberant environments, the adaptive eigenvalue decomposition based time delay estimation method is studied.
     为了将该思路推广到不相关噪声情况,本文给出一种基于噪声类型判别的传声器阵列语音活动检测方法。
短句来源
更多       
  相似匹配句对
     Activities
     活动
短句来源
     CCUA ACTIVITIES
     协会活动
短句来源
     Improved Voice Activity Detector Based on the Wavelet Transform
     改进的基于小波变换的语音活动检测算法
短句来源
     Closed eye movements in schizophrenic patients under verbal and musical stimulation.
     精神分裂症语音和音乐刺激时的闭眼眼球活动
短句来源
     Phonetic Analysis
     语音分析
短句来源
查询“语音活动”译词为用户自定义的双语例句

    我想查看译文中含有:的双语例句
例句
为了更好的帮助您理解掌握查询词或其译词在地道英语中的实际用法,我们为您准备了出自英文原文的大量英语例句,供您参考。
  voice activity
In speech signal processing systems, frame-energy based voice activity detection (VAD) method may be interfered with the background noise and non-stationary characteristic of the frame-energy in voice segment.
      
The capacity of mobile communication system is improved by using Voice Activity Detection (VAD) technology.
      
A Robust, Real-Time Voice Activity Detection Algorithm for Embedded Mobile Devices
      
When an Automatic Speech Recognition (ASR) system is applied in noisy environments, Voice Activity Detection (VAD) is crucial to the performance of the overall system.
      
This is followed by an investigation of traffic source model effects: first the capacity improvement from voice activity detection VAD) is presented, showing the expected ~2∶1 gains.
      
更多          


Owing to the flexibility of time_frequency resolution of wavelet transform,we present an improved voice activity detector (VAD) based on wavelet transform.Robust parameters in different scale and time resolution are computed for VAD decision,such as silence measure,stability measure of amplitude spectrum between adjacent frames,background noise measure of different frequency band,time_domain stability measure of scale 1. The silence measure is used to detect the existence of silence in the input frame.The stability...

Owing to the flexibility of time_frequency resolution of wavelet transform,we present an improved voice activity detector (VAD) based on wavelet transform.Robust parameters in different scale and time resolution are computed for VAD decision,such as silence measure,stability measure of amplitude spectrum between adjacent frames,background noise measure of different frequency band,time_domain stability measure of scale 1. The silence measure is used to detect the existence of silence in the input frame.The stability measure of amplitude spectrum between adjacent frames is adopted to give a rough decision of the detection of stable noise based on the assumption that background noise is stable.If current input frame is noise,the energy of every frequency band is below the average of background noise energy threshold over long time.We divide the signal bandwidth into several scales by wavelet transform,and calculate the background noise measure of different scale.In low scale the input signal changes rapidly,and the variety of short time energy will be removed with long window.We calculate the mean square error of short time energy,and get time_domain stability measure from detail coefficients of scale 1.With these measures,we make the VAD decision. Compared with G.729 Annex B,the authors can detect the voice activity more accurately and reduce the ratio of speech clipping using the new algorithm.And the improved algorithm can achieve robust performance for different background noise,even in serious low signal_to_noise environment about 10dB.

提出了一种改进的基于小波变换的语音活动检测算法。这种新算法能够在不同的时间和尺度上计算用于语音活动检测的参数 ,根据这些参数得到稳健的语音活动决策。实验表明 ,新算法与ITUG .72 9附录B相比 ,能够更准确地检测到语音活动 ,语音活动剪切率大为减少 ;同时新算法对于不同类型的背景噪声 ,即使全局信噪比在 10dB以下也具有较好的性能。

This article has summarized the A coustic-Echo Cancellation technique in Internet audio communication.It describes the DSP implementation algorithm of a full-duplex Acoustic-Echo Cancellation (AEC) software.This implementation is based on the Normalized Least Mean Square(NLMS) algorithm.The algorithm includes double-talk detection.

文章概述了 Internet语音通信技术中的回声消除技术 ,描述了一个全双工的声学回声消除器软件的 DSP实现算法。这个实现是基于规格化最小均方差 ( NLMS)的算法 ,包括双端语音活动检测的原理。

In order to identify the voice activity accurately in a background of 100-115dB high noise, voice signals were interpreted by using a circuit based on the DSPF801 chip produced by the Motorola. The voice detection algorithm used in the circuit could adjust threshold automatically according to the change of noise signals, which ensured a normal communication of the whole system. The test results showed that the detection rate reached 100%, 96% and 94% corresponding the noise levels of 100, 110 and 115dB respectively;...

In order to identify the voice activity accurately in a background of 100-115dB high noise, voice signals were interpreted by using a circuit based on the DSPF801 chip produced by the Motorola. The voice detection algorithm used in the circuit could adjust threshold automatically according to the change of noise signals, which ensured a normal communication of the whole system. The test results showed that the detection rate reached 100%, 96% and 94% corresponding the noise levels of 100, 110 and 115dB respectively; and the words loss rate were 2%, 5% and 10% respectively. The system stability reached 100% and 98% respectively in high noise background of 100-110dB and 110-115dB. The system ability on anti-jamming was improved and a precision detection of VD was implemented in a high noise background or to unstable noise signals by the developed algorithm.

以MOTOROLA公司生产的DSP56F801芯片为核心搭建系统硬件电路,对语音信号进行处理。采用能够根据背景噪声变化而自适应调节门限的算法对语音活动进行精确检测,实现整机系统在高噪声环境下的正常通讯。实际检测结果表明:在100、110、115dB的强背景噪声环境下,系统识别率分别为100%、96%和94%,丢字漏字率分别为2%、5%和10%;在100~110、110~115dB的背景噪声环境,系统稳定性分别为100%和98%。采用此种算法,增强了系统的抗干扰能力,在高噪声和噪声不太稳定的环境下,实现了对语音活动的精确检测。

 
<< 更多相关文摘    
图标索引 相关查询

 


 
CNKI小工具
在英文学术搜索中查有关语音活动的内容
在知识搜索中查有关语音活动的内容
在数字搜索中查有关语音活动的内容
在概念知识元中查有关语音活动的内容
在学术趋势中查有关语音活动的内容
 
 

CNKI主页设CNKI翻译助手为主页 | 收藏CNKI翻译助手 | 广告服务 | 英文学术搜索
版权图标  2008 CNKI-中国知网
京ICP证040431号 互联网出版许可证 新出网证(京)字008号
北京市公安局海淀分局 备案号:110 1081725
版权图标 2008中国知网(cnki) 中国学术期刊(光盘版)电子杂志社