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pyAudioAnalysis:一个用于音频信号分析的开源Python库。

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

作者信息

Giannakopoulos Theodoros

机构信息

Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, NCSR Demokritos, Patriarchou Grigoriou and Neapoleos St, Aghia Paraskevi, Athens, 15310, Greece.

出版信息

PLoS One. 2015 Dec 11;10(12):e0144610. doi: 10.1371/journal.pone.0144610. eCollection 2015.

Abstract

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 (https://github.com/tyiannak/pyAudioAnalysis/). 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.

摘要

音频信息在如今日益增长的数字内容中扮演着相当重要的角色,这就导致需要能够自动分析此类内容的方法:用于家庭自动化和监控系统的音频事件识别、语音识别、音乐信息检索、多模态分析(例如基于内容推荐的在线视频的视听分析)等。本文介绍了pyAudioAnalysis,这是一个开源的Python库,它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以及内容可视化。pyAudioAnalysis遵循Apache许可协议,可在GitHub(https://github.com/tyiannak/pyAudioAnalysis/)上获取。在此,我们介绍所实现的各种方法背后的理论背景,以及其中一些方法的评估指标。pyAudioAnalysis已经在多个音频分析研究应用中得到使用:通过音频事件检测实现智能家居功能、语音情感识别、基于视听特征的抑郁症分类、音乐分割、基于多模态内容的电影推荐以及健康应用(例如饮食习惯监测)。所有这些特定音频应用提供的反馈促使该库得到了实际改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/098a/4676707/cea36c494067/pone.0144610.g001.jpg

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