Metadata-Version: 1.1
Name: attk
Version: 0.0.5
Summary: Audio Tagging Toolkit: A collection of scripts to expedite audio annotation and classifier training.
Home-page: https://github.com/hipstas/audio-tagging-toolkit
Author: Stephen Reid McLaughlin
Author-email: stephen.mclaughlin@utexas.edu
License: Apache 2.0
Description: 
        ### Mac Installation
        
        
        Install Audio Tagging Toolkit using pip:
        
        ```bash
        pip install git+git://github.com/hipstas/audio-tagging-toolkit.git
        ```
        
        Next we will install **`ffmpeg`**, a command-line tool for audio and video encoding. First we will install several media codecs and command-line tools, then we will download ffmpeg's source code and compile it before installing. If you've previously installed ffmpeg using Homebrew, uninstall that copy before we begin:
        
        ```bash
        brew uninstall ffmpeg
        ```
        
        Enter the following commands one at a time; note that the first and fourth lines are very long. After the last command you will be prompted to enter your password.
        
        ```
        brew install automake fdk-aac git lame libass libtool libvorbis libvpx opus sdl shtool texi2html theora wget x264 xvid yasm
        
        git clone http://source.ffmpeg.org/git/ffmpeg.git ffmpeg
        
        cd ffmpeg
        
        ./configure  --prefix=/usr/local --enable-gpl --enable-nonfree --enable-libass --enable-libfdk-aac --enable-libfreetype --enable-libmp3lame --enable-libopus --enable-libtheora --enable-libvorbis --enable-libvpx --enable-libx264 --enable-libxvid
        
        make && sudo make install
        ```
        
        
        
        ### Install Ubuntu dependencies:
        
        ```bash
        apt-get update -y && apt-get upgrade -y
        sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
        sudo apt-get -y install swig
        sudo apt-get -y install libpulse-dev
        
        pip install -U pip
        pip install virtualenv
        
        #Install FFmpeg with MP3 support (at your own risk):
        
        sudo add-apt-repository -y ppa:mc3man/trusty-media
        sudo apt-get update
        sudo apt-get -y dist-upgrade
        sudo apt-get -y install ffmpeg
        ```
        
        Now install Audio Tagging Toolkit using pip:
        
        ```bash
        pip install git+git://github.com/hipstas/audio-tagging-toolkit.git
        ```
        
        
        
        
        
        ### Script examples via bash
        
        - Locate applause in single file, with non-applause segments labeled "Speaker Name" and a 2-second buffer on either side of each transition:
        
        ```bash
        cd /path/to/audio-tagging-toolkit
        
        python FindApplause.py -c -b 2 -l "Speaker Name" -i /path/to/audio.mp3
        ```
        
        - Batch applause classification with CSV output, default 1-second buffer, and label for non-applause regions:
        
        ```bash
        cd /path/to/audio-tagging-toolkit
        
        python FindApplause.py -c -b -l "Speaker Name" /path/to/directory/
        ```
        
        - Diarize a single file:
        
        ```bash
        cd /path/to/audio-tagging-toolkit
        
        python Diarize.py -b -c -i /Users/mclaugh/Desktop/attktest/Creeley-Robert_33_A-Note_Rockdrill-2.mp3
        ```
        
        - Batch Diarize:
        
        ```bash
        cd /path/to/audio-tagging-toolkit
        
        python Diarize.py -b -c /Users/mclaugh/Desktop/attktest/
        ```
        
        - Excerpt a class:
        
        ```bash
        
        cd /Users/mclaugh/Dropbox/WGBH_ARLO_Project/audio-tagging-toolkit/
        
        for f in /Volumes/Turcich-2012/AAPB_Test_Haystack/*_king_gradientboosting.csv; do
        base=$(basename """$f""" _king_gradientboosting.csv)
        python ExcerptClass.py -i """/Volumes/Turcich-2012/AAPB_Test_Haystack/$base.mp3""" -t """$f""" -e 0 -o "/Volumes/Turcich-2012/AAPB_excerpt_output/";
        done
        
        for f in /Volumes/Turcich-2012/AAPB_Test_Haystack/*_king_gradientboosting.csv; do
        base=$(basename """$f""" _king_gradientboosting.csv)
        python ExcerptClass.py -i """/Volumes/Turcich-2012/AAPB_Test_Haystack/$base.mp4""" -t """$f""" -e 0 -o "/Volumes/Turcich-2012/AAPB_excerpt_output/";
        done
        ```
        
        - Excerpt from MP4s only:
        
        ```bash
        cd /Users/mclaugh/Dropbox/WGBH_ARLO_Project/audio-tagging-toolkit/
        
        for f in /Volumes/Turcich-2012/AAPB_Test_Haystack/*.mp4; do
        base=$(basename """$f""" .mp4)
        command="""python ExcerptClass.py -i "/Volumes/Turcich-2012/AAPB_Test_Haystack/$base.mp4" -t "/Volumes/Turcich-2012/AAPB_Test_Haystack/${base}_king_gradientboosting.csv" -e 0 -o "/Volumes/Turcich-2012/AAPB_excerpt_output/" """;
        echo $command
        eval $command;
        done
        ```
        
        - Launch QuickCheck script to rapidly review applause/speaker labels in Sonic Visualiser:
        
        ```bash
        cd /path/to/audio-tagging-toolkit
        python QuickCheck.py -a -v -i /path/to/audio/files
        ```
        
        - QuickCheck diarization mode:
        
        
        ```bash
        cd /path/to/audio-tagging-toolkit
        python QuickCheck.py -d -v -i /path/to/audio/files
        ```
        
        - Assign random tags:
        
        ```bash
        python RandomTags.py -s 3 -n 3 -e -i /path/to/example.mp3 -o /path/to/output_dir/
        ```
        
Keywords: audio music speech classification tagging labeling ml supervised
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
