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        "description": "[![Build Status](https://travis-ci.org/EliosMolina/audio_degrader.svg?branch=master)](https://travis-ci.org/EliosMolina/audio_degrader)\n# audio_degrader\n\nLatest version: `1.2.3`\n\nAudio degradation toolbox in python, with a command-line tool. It is useful to apply controlled degradations to audio.\n\n\n## Installation\n\n`pip install audio_degrader`\n\nThe program depends on `sox`, `ffmpeg` and `rubberband`, so you might need to install them as well. Recommended `brew` in OSX and `apt-get` in linux (for rubberband, in linux use `rubberband-cli`).\n\n\n## Usage of python package\n```Python\nimport audio_degrader as ad\naudio_file = ad.AudioFile('input.wav', './tmp_dir')\nfor d in ad.ALL_DEGRADATIONS.values():\n    print ad.DegradationUsageDocGenerator.get_degradation_help(d)\ndegradations = ad.ParametersParser.parse_degradations_args([\n    'normalize',\n    'gain,6',\n    'dr_compression,3',\n    'equalize,500,10,30'])\nfor d in degradations:\n    audio_file.apply_degradation(d)\naudio_file.to_wav('output.wav')\naudio_file.delete_tmp_files()\n```\n\n## Usage of command-line tool\n\nThe script `audio_degrader` is installed along with the python package.\n\n```\n# e.g. mix with restaurant08.wav with snr=10db, then amplifies 6db, then compress dynamic range\n$ audio_degrader -i input.mp3 -d mix,https://github.com/hagenw/audio-degradation-toolbox/raw/master/AudioDegradationToolbox/degradationData/PubSounds/restaurant08.wav,10 gain,6 dr_compression,3 -o out.wav\n\n# for more details:\n$ audio_degrader --help\n```\n\nA small set of sounds and impulse responses are installed along with the script, which can be listed with:\n```\n$ audio_degrader -l\n\n# these relative paths can be used directly in the script too:\n$ audio_degrader -i input.mp3 -d mix,sounds/applause.wav,-3 gain,6 -o out.wav\n```\n\n\n## Applications\n* Evaluate Music Information Retrieval systems under different degrees of degradations\n* Prepare augmented data for training of machine learning systems\n\nIt is similar to the [Audio Degradation Toolbox in Matlab by Sebastian Ewert and Matthias Mauch][1] (for Matlab).\n\n\n## Some examples\n\n```\n# Mix input with a sound / noise (e.g. using installed resources)\n$ audio_degrader -i input.wav -d mix,sounds/applause.wav,-3 -o out.wav\n\n\n# Instead of paths, we can also use URLs\n$ audio_degrader -i input.wav -d mix,https://www.pacdv.com/sounds/ambience_sounds/airport-security-1.mp3,-3 -o out.wav\n\n\n# Microphone recording style\n$ audio_degrader -i input.wav -d gain,-15 mix,sounds/ambience-pub.wav,18 convolution,impulse_responses/ir_smartphone_mic_mono.wav,0.8 dr_compression,2 equalize,50,100,-6 normalize -o out.wav\n\n\n# Resample and normalize\n$ audio_degrader -i input.mp3 -d resample,8000 normalize -o out.wav\n\n\n# Convolution (again impulse responses can be resources, full paths or URLs)\n$ audio_degrader -i input.wav -d convolution,impulse_responses/ir_classroom_mono.wav,0.7 -o out.wav\n$ audio_degrader -i input.wav -d convolution,http://www.cksde.com/sounds/month_ir/FLANGERSPACE%20E001%20M2S.wav,0.7 -o out.wav\n```\n\n## Audio formats\n\n### Input\n`audio_degrader` relies on ffmpeg for audio reading, so it can read any format (even video).\n\n### Output\n`audio_degrader` output format is always wav stereo `pcm_f32le` (sample rate from original audio file).\n\nThis output wav file can be easily coverted into another format with ffmpeg, e.g.:\n```\n$ ffmpeg -i out.wav -b:a 320k out.mp3\n$ ffmpeg -i out.wav -ac 2 -ar 44100 -acodec pcm_s16le out_formatted.wav\n```\n\n\n[1]: https://code.soundsoftware.ac.uk/projects/audio-degradation-toolbox\n\n\n",
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