基于语音/音乐识别的智能音频编码专家系统

J. E. M. Expósito, S. G. Galán, Nicolas Ruiz Reyes, P. V. Candeas, F. Pena
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引用次数: 3

摘要

语音/音乐自动识别已成为近年来的研究热点。提出了一种基于专家系统的语音/音乐识别新方法,该方法将模糊规则融入到专家系统的知识库中。该方案包括三个阶段:1)特征提取,2)音频信号分类,3)每23 ms选择最佳音频编码器。将模糊专家系统引入分类阶段,提高了GMM分类器的准确率。为了选择最佳的音频编码器,专家系统考虑了当前帧和过去帧的信息。需要强调的是,所提出的方法的低计算成本使其适用于实时应用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expert system for intelligent audio codification based in speech/music discrimination
Automatic speech/music discrimination has become a research topic of interest in the last years. This paper presents a new approach for speech/music discrimination, which is based on an expert system that incorporates fuzzy rules into its knowledge base. The proposed scheme consists of three stages: 1) features extraction, 2) audio signal classification, and 3) selection of the best audio coder every 23 ms. The fuzzy expert system improves the accuracy rate of a GMM classifier when included into the classification stage. In order to select the best audio coder, the expert system takes information of the current and past frames into account. It is important to emphasize that the low computational cost of the proposed approach makes it feasible for real time applications
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