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噪声帧
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  noise frames
     This paper presents the formula of the speech quality evaluation incorporating the Bark spectrum distortion and the ratio of the muted and noise frames. Calculational results are comparied with the mean opinion score (MOS).
     文中同时给出了结合巴克谱失真和弱音与噪声帧比率的语音质量评估公式 ,并将计算结果与平均意见分 (MOS)进行了比较。
短句来源
     What’s more, the transition frames are divided into different groups in detail based on energy. With a further improved method of spectral subtraction, speech frames, transition frames, and noise frames are processed separately to get rid of music noise.
     对谱减法做进一步改进,以能量为基础对过渡帧进行细分,对语音帧、过渡帧、噪声帧分别进行不同的处理,从而克服了令人厌烦的音乐噪声,在强航空噪声背景下,处理后的语音不仅信噪比得到了很大的提高,而且清晰度和可懂度也得到了很大的改善。
短句来源
  “噪声帧”译为未确定词的双语例句
     This paper introduces the speech enhancement algorithm based on the Minimum Mean-Square Error Short-Time Log-Spectral Amplitude Estimation (MMSE-LSA) under the single input condition as well as the method for distinguishing between speech and noise frame.
     介绍了单话筒采集条件下基于语音短时对数谱的最小均方误差(MMSE-LSA)估计的语音增强算法,以及语音帧和噪声帧判别的有声/无声检测方法。
短句来源
     The frame energy and the sub-band energy were used to calculate the discrimination information based on the sub-band energy distribution probabilities both for the current frame and the noise frame.
     该算法利用帧信号的能量、子带信号的能量等参数,计算该帧信号与噪声帧基于子带能量分布概率的鉴别信息。
短句来源
     According to the traditional spectral subtraction and speech enhancement algorithm, a new improved spectral subtraction algorithm has been put forward to restrain noises. This method gives different spectral estimate values α and β based on the signal spectral power and uses spectral subtraction to realize speech enhancement.
     根据传统的谱相减增强型算法 ,提出了抑制噪声的谱减改进算法 ,暨根据带噪语音帧频谱功率与噪声帧频谱功率比值 ,动态调整α、β谱减系数 ,使之谱减效果在较大提高信噪比的同时 ,又能将残留的音乐噪声和语音失真保持在人耳听觉的容忍范围之内 ,保证原始语音信号质量达到一定的可懂度和清晰度。
短句来源
     The types of additive noise are to be ascertained firstly according to the differences in the spectrum amplitude between white noise(including color noise with flatting spectrum amplitude) and color noise with varying spectrum amplitude.
     根据噪声帧频谱的平整度判断出噪声的类型,即是白噪声(含频响曲线比较平整的有色噪声)还是频响曲线不平整的有色噪声.
短句来源
     The noise estimation is updated in both speech frame and noise frame without the voice activity detection.
     不采用端点检测,在语音帧内及噪声帧内都进行噪声更新。
短句来源
  相似匹配句对
     LOW LIGHT LEVEL IMAGE PROCESSING WITH THE METHOD OF FRAME INTEGRAL
     利用积分法去除微光图像噪声研究
短句来源
     Low Light Level Image Processing with the Method of Frame Integral
     利用积分法去除微光图像噪声研究
短句来源
     A recommended acceptable noise level can be determined from the teacheras response to the noise under investigation.
     噪声调查;
短句来源
     WHITE NOISE
     白噪声
短句来源
     The Frame Relay Switched Technologies
     中继交换技术
短句来源
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  noise frames
Considering one-way communication, six different operating rates can be externally selected ranging from 4.8 to 9.1 kbps for the active frames; an average bit rate of 380 bps is required for the noise frames.
      
The method found all the intended gestures cycles except for a few individual cycles that had multiple noise frames.
      
The noise spectrum tilt is the coefficient from first order LP analysis of the noise frames.
      


According to the traditional spectral subtraction and speech enhancement algorithm, a new improved spectral subtraction algorithm has been put forward to restrain noises. This method gives different spectral estimate values α and β based on the signal spectral power and uses spectral subtraction to realize speech enhancement. At last Emulation by means of the MATLAB language and its analysis result have been given in detail.

根据传统的谱相减增强型算法 ,提出了抑制噪声的谱减改进算法 ,暨根据带噪语音帧频谱功率与噪声帧频谱功率比值 ,动态调整α、β谱减系数 ,使之谱减效果在较大提高信噪比的同时 ,又能将残留的音乐噪声和语音失真保持在人耳听觉的容忍范围之内 ,保证原始语音信号质量达到一定的可懂度和清晰度。借助MATLAB语言进行试验仿真 ,仿真结果与原算法相比较 ,证明语音增强效果十分显著

An algorithm for objectively evaluating the subjective quality of speech is presented. The algorithm calculates the distortion between the original and the reconstructed signals in Bark spectrum domain and takes the effects into account which the muted and noise frames impose on the speech quality evaluation. This paper presents the formula of the speech quality evaluation incorporating the Bark spectrum distortion and the ratio of the muted and noise frames. Calculational results are comparied with the mean...

An algorithm for objectively evaluating the subjective quality of speech is presented. The algorithm calculates the distortion between the original and the reconstructed signals in Bark spectrum domain and takes the effects into account which the muted and noise frames impose on the speech quality evaluation. This paper presents the formula of the speech quality evaluation incorporating the Bark spectrum distortion and the ratio of the muted and noise frames. Calculational results are comparied with the mean opinion score (MOS). Numerical experiments show that the improved Bark spectrum distortion (IBSD) measurement is highly correlated with MOS. IBSD can estimate the subjective quality of the speech signal. The IBSD can be used in various systems of speech coder and speech communication.

提出了一种语音主观质量的客观评估算法 ,该算法在巴克谱的基础上计算原始语音与重建语音之间的失真度 ,并考虑了弱音帧与噪声帧的存在对语音质量评估的影响。文中同时给出了结合巴克谱失真和弱音与噪声帧比率的语音质量评估公式 ,并将计算结果与平均意见分 (MOS)进行了比较。数值实验表明 ,本文提出的增强型巴克谱失真测度 (IBSD)与 MOS之间具有很强的相关性 ,能客观地评价出语音信号的主观质量 ,适用于各种语音编码、语音通信系统。

This paper introduces the speech enhancement algorithm based on the Minimum Mean-Square Error Short-Time Log-Spectral Amplitude Estimation (MMSE-LSA) under the single input condition as well as the method for distinguishing between speech and noise frame. The phase of the speech signal is stored and the amplitude is estimated using the MMSE-LSA. The signal processed is reconstructed with the amplitude estimated and the phase stored. Experiments show that the algorithm has good performance in speech enhancement,...

This paper introduces the speech enhancement algorithm based on the Minimum Mean-Square Error Short-Time Log-Spectral Amplitude Estimation (MMSE-LSA) under the single input condition as well as the method for distinguishing between speech and noise frame. The phase of the speech signal is stored and the amplitude is estimated using the MMSE-LSA. The signal processed is reconstructed with the amplitude estimated and the phase stored. Experiments show that the algorithm has good performance in speech enhancement, especially when the SNR is low.

介绍了单话筒采集条件下基于语音短时对数谱的最小均方误差(MMSE-LSA)估计的语音增强算法,以及语音帧和噪声帧判别的有声/无声检测方法。将语音信号的相位提取后存储起来,然后对纯净语音的短时对数谱作最小均方误差估计,处理后的语音由估计得到的幅度谱和存储的相位重建。试验证明MMSE-LSA的增强效果很好,尤其在信噪比低时更为明显。

 
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