外文翻译--音频事件识别特征核

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1、2600单词， 1.3万英文字符， 4400汉字 出处： Kumar A, Raj B. Features and kernels for audio event recognitionJ. arXiv preprint arXiv:1607.05765, 2016. 毕业设计外文翻译 （原文及译文） 原文名称： Features and Kernels for Audio Event Recognition 学 生 姓 名 学 号 指 导 教 师 所 在 系 部 专 业 名 称 2017 年 3 月 7日 Features and Kernels for Audio Event Recogn

2、ition A Kumar ， B Raj Abstract One of the most important problems in audio event detection research is absence of benchmark results for comparison with any proposed method. Different works consider different sets of events and datasets which makes it difficult to comprehensively analyze any novel me

3、thod with an existing one. In this paper we propose to establish results for audio event recognition on two recent publicly-available datasets. In particular we use Gaussian Mixture model based feature representation and combine them with linear as well as non-linear kernel Support Vector Machines.

4、Index Terms: Audio Event Detection, Audio Content Analysis. 1. Introduction In recent years automatic content analysis of audio recordings has been gaining attention among the audio research community. The goal is to develop methods which can automatically detect the presence of different kinds of a

5、udio events in a recording. Audio event detection (AED) research is driven by its application in several areas. These include areas such as multimedia information retrieval or multimedia event detection1 where the audio component contains important information about the content of the multimedia data. This is particularly important for supporting content-based search and retrieval of multimedia data on the web. Other applications such as surveillance 2, wildlife monitoring 3 4, context aware systems 5 6, health monitoring etc. are also motivating audio event detection research. A variety of