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Frequency-Temporal Filtering for a Robust Audio Fingerprinting Scheme in Real-Noise Environments

机译:实时噪声环境中鲁棒音频指纹方案的时频滤波

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In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-pass filtering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips’ audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.
机译:在真实环境中,录音通常会因声道和背景噪声而失真,而音频识别的性能主要会因录音和声道而变差。最近,飞利浦推出了一种稳健而高效的音频指纹识别方案,该方案将差分(高通滤波)应用于感知滤波器组能量的频率-时间序列。然而,实际上,音频指纹方案的鲁棒性在实际环境中仍然很重要。在这封信中,我们为飞利浦音频指纹识别方案的扩展方法介绍了时空滤波组合的替代方案,以在真实情况下实现对通道和背景噪声的鲁棒性。我们的实验结果表明,提出的滤波组合提高了音频识别中的噪声鲁棒性。

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