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基音检测是河南方言语音信号处理中的一个重要环节,针对低信噪比环境下的河南方言语音基音检测准确率低的问题,提出了一种语音信号增强和基音检测相结合的算法.通过多窗谱估计的改进谱减法对语音信号进行降噪处理,对增强后的语音信号用中心削波法消除偏离基音轨迹的野点,再通过自相关法实现基音检测.仿真结果表明,对于低信噪比环境下河南方言语音信号的基音估值检测结果准确,估算出的基音频率和实际基音频率能很好的重合. 相似文献
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基于形态滤波和小波变换的基音检测新方法 总被引:2,自引:1,他引:1
提出了一种基于数学形态滤波和小波变换相结合的基音检测方法。检测前采用文中提出的形态滤波算法对噪声信号进行滤除,突出了基音周期。用小波变换对滤波后语音信号的突变点进行检测,进而提取出了基音周期。实验表明该方法对噪声有较强的鲁棒性,能够精确地检测出基音周期。 相似文献
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针对语音信号在小信噪比条件下检测其基音周期。考虑自适应滤波和小波变换的优点对小信噪比条件下的语音信号进行基音周期检测,实验证明此方法能有效检测-20dB下的基音周期。 相似文献
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本文提出了一种基于线性预测残差倒谱的多语音基音频率检测算法,该算法首先对混合语音信号进行线性预测分析,进而计算预测信号与原混合信号的残差,并对残差信号做倒谱变换,得到混合语音信号的线性预测残差倒谱;然后在该信号的残差倒谱中,结合图像处理的技术,利用语音信号基音倒频匹配法检测出多语音信号的基音频率;最后在基音标定的过程中,本文算法利用语音信号的连续特性,依据信号基音频率前后差距变化最小原则标记出各基音所属话者。实验结果表明,本文提出的算法在弱回声及无回声的情况下能快速有效地从单声道混合语音信号中检测出多语音基音信息。 相似文献
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本文提出了一种新的语音信号的基音周期检测方法,该方法根据语音信号的三阶累积量去确定语音信号的基音周期,能有效地排除白色或有色的高斯加性噪声所带来的干扰.与传统的基音周期估计的自相关函数法或平均幅度差函数法(AMDF)相比,该方法更精确、有效,具有更强的鲁棒性. 相似文献
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This paper discusses robust speech section detection by audio and video modalities. Most of today's speech recognition systems require speech section detection prior to any further analysis, and the accuracy of detected speech section s is said to affect the speech recognition accuracy. Because audio modalities are intrinsically disturbed by audio noise, we have been researching video modality speech section detection by detecting deformations in speech organ images. Video modalities are robust to audio noise, but their detection sections are longer than audio speech sections because deformations in related organs start before the speech to prepare for the articulation of the first phoneme, and also because the settling down motion lasts longer than the speech. We have verified that inaccurate detected sections caused by this excess length degrade the speech recognition rate, leading to speech recognition errors by insertions. To reduce insertion errors, and enhance the robustness of speech detection, we propose a method that takes advantage of the two types of modalities. According to our experiment, the proposed method is confirmed to reduce the insertion error rate as well as increase the recognition rate in noisy environment. 相似文献
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在车内数字通信系统中,使用基于DSP嵌入式的以太局域网,实现车内语音和数据同传通信。笔者设计该系统时的重点是在语音数字处理,特别提出了一种自行设计的语音起止点判决方法--五点搜索法。 相似文献
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Anil Kumar Vuppala K. Sreenivasa Rao Saswat Chakrabarti 《AEUE-International Journal of Electronics and Communications》2012,66(8):697-700
Vowel onset point (VOP) is the instant at which the onset of vowel takes place in the speech signal. Accurate detection of VOP is useful for applications such as consonant–vowel (CV) unit recognition and speech rate modification. Existing VOP detection methods determine VOPs within 40 ms deviation, which may not be suitable for the applications mentioned above. In this paper, a two level approach using multiple sources of evidence is proposed for the accurate detection of VOP. In the proposed method, at the first level, VOPs are identified by combining the complementary evidence from excitation source, spectral peaks and modulation spectrum. At the second level, hypothesized VOPs are verified (genuine or spurious), and their positions are corrected using the uniform epoch intervals present in vowel region. Zero frequency filter method is used to determine the epoch locations in speech. Performance of the proposed method is analyzed using TIMIT database, and compared with the recent method which uses the combination of evidence from excitation source, spectral peaks and modulation spectrum. Using the proposed method about 85% of VOPs are detected within 10 ms deviation. 相似文献
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In this paper, we propose the use of data‐driven probabilistic utterance‐level decision logic to improve Weighted Finite State Transducer (WFST)‐based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame‐level speech/non‐speech classification based on statistical hypothesis testing, and the second process is a heuristic‐knowledge‐based utterance‐level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST‐based approach. However, a WFST‐based approach has the same limitations as conventional approaches in that the utterance‐level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data‐driven probabilistic utterance‐level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy‐speech corpora collected for an endpoint detection evaluation. 相似文献
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该文提出了分段线性动态系统周期轨道的时域法求解及稳定性判断的新方法。分段线性动态系统的状态空间被切换面分割成若干个线性子区间。借助MATLAB,联合求解周期轨道在各子区间的状态转移方程,可得该周期轨道在各切换面的切换点坐标及在各子区间的运行时间,从而得到该周期轨道的分段时间表达式。由该表达式,可导出该周期轨道在某一切换面的庞加莱映射方程及其雅可比矩阵,根据其特征值可判断周期轨道的稳定性。以三阶、四阶蔡氏电路为例,用该方法求出了它们的多个周期轨道,进行了稳定性判断,数字仿真表明该文所提出的新方法是可行的和正确的。 相似文献