英语翻译Abstract—An effective voice activity detection (VAD) alg

英语翻译
Abstract—An effective voice activity detection (VAD) algorithm
is proposed for improving speech recognition performance in
noisy environments.The approach is based on the determination
of the speech/nonspeech divergence by means of specialized order
statistics filters (OSFs) working on the subband log-energies.
This algorithm differs from many others in the way the decision
rule is formulated.Instead of making the decision based on the
current frame,it uses OSFs on the subband log-energies which
significantly reduces the error probability when discriminating
speech from nonspeech in a noisy signal.Clear improvements
in speech/nonspeech discrimination accuracy demonstrate the
effectiveness of the proposed VAD.It is shown that an increase of
the OSF order leads to a better separation of the speech and noise
distributions,thus allowing a more effective discrimination and
a tradeoff between complexity and performance.The algorithm
also incorporates a noise reduction block working in tandem with
the VAD and showed to further improve its accuracy.A previous
noise reduction block also improves the accuracy in detecting
speech and nonspeech.The experimental analysis carried out on
the AURORA databases and tasks provides an extensive performance
evaluation together with an exhaustive comparison to the
standard VADs such as ITU G.729,GSM AMR,and ETSI AFE for
distributed speech recognition (DSR),and other recently reported
VADs.
Index Terms—Noise reduction,robust speech recognition,
speech/nonspeech detection,subband order statistics filters.

抽象的一个有效的语音活动检测（VAD）算法
提出了提高语音识别性能
嘈杂的环境.该方法是基于对测定
由专门的命令意味着语音/ nonspeech分歧
统计滤波器（性质,OSFS）关于子带日志精力工作.
该算法不同于许多其他的方式的决定
规则的制订.而不是作出决定的基础上
当前帧,它使用的频带数的能量性质,OSFS
大大减少了错误的概率时歧视
从nonspeech讲话在嘈杂的信号.明显改善
在语音/ nonspeech歧视准确性展示
建议VAD方案的有效性.结果表明,增加的一
在OSF秩序导致了更好的语音和噪声分离
分布,从而使一个更加有效的歧视和
复杂性和性能之间的权衡.该算法
还集成了降噪块串联与
VAD与表明的,以进一步提高其准确性.阿前
降噪区块还提高了检测的准确性
言论和nonspeech.实验进行了分析
震旦的数据库和任务提供了广泛的性能
连同一份详尽的评估相比,
例如国际电联G.729的,GSM的AMR的,外汇局和ETSI标准威斯为
分布式语音识别（DSR路由）,和其他最近报告
威斯.
指数计算,噪声降低,稳健语音识别,
语音/ nonspeech检测,子带顺序统计滤波器.