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pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis

机译:pyAudioAnalysis:用于音频信号分析的开源Python库

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摘要

Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library.
机译:音频信息在当今日益增长的数字内容中起着相当重要的作用,因此需要一种自动分析此类内容的方法:用于家庭自动化和监视系统的音频事件识别,语音识别,音乐信息检索,多模式分析(例如在线视频的视听分析,以基于内容的推荐为基础)等等。本文介绍了pyAudioAnalysis,这是一个开源Python库,提供了广泛的音频分析程序,包括:特征提取,音频信号分类,有监督和无监督分割和内容可视化。 pyAudioAnalysis已获得Apache许可的许可,可从GitHub()获得。在这里,我们介绍了广泛实施的方法论背后的理论背景,以及一些方法的评估指标。 pyAudioAnalysis已用于多种音频分析研究应用程序:通过音频事件检测的智能家居功能,语音情感识别,基于视听功能的抑郁症分类,音乐分割,基于多模式内容的电影推荐以及健康应用程序(例如监控饮食)习惯)。所有这些特定音频应用程序提供的反馈已导致库的实际增强。

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