基于噪声鲁棒性内容的音乐检索系统

Won-Jung Yoon, Kyusik Park
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引用次数: 1

摘要

本文构建了基于噪声鲁棒性的基于内容的音乐检索系统。利用ZCPA特征验证了系统的性能,该特征在语音识别应用中具有噪声鲁棒性。此外,提出了新的索引和快速检索方法,与穷举检索相比,检索速度提高了99%。在15dB ~ 0dB信噪比噪声环境下的计算机仿真结果表明,与MFCC和FBE(滤波器组能量)相比,该系统的性能提高了5% ~ 30%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A noise robust content-based music retrieval system
In this paper, we constructed the noise robust content-based music retrieval system. The performance of the proposed system was verified with ZCPA feature, which is known to have noise robust characteristic in speech recognition application. In addition, new indexing and fast retrieval method were proposed to improve retrieval speed about 99% compare to exhaustive retrieval for large music DB. From the computer simulation results in noise environment of 15dB − 0dB SNR, we confirmed the superior performance of the proposed system about 5% – 30% compared to MFCC and FBE (filter bank energy).
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