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        "author": "Tim Mahrt",
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        "description": "\n-------------\npyAcoustics\n-------------\n\n.. image:: https://img.shields.io/badge/license-MIT-blue.svg?\n   :target: http://opensource.org/licenses/MIT\n\nA collection of python scripts for extracting and analyzing acoustics from audio files.\n\n.. sectnum::\n.. contents::\n\nCommon Use Cases\n================\n\nWhat can you do with this library?\n\n- Extract pitch and intensity::\n\n    pyacoustics.intensity_and_pitch.praat_pi.getPraatPitchAndIntensity()\n\n- Extract segments of a wav file::\n\n    pyacoustics.signals.audio_scripts.getSubwav()\n\n- Perform simple manipulations on wav files::\n\n    pyacoustics.signals.resampleAudio()\n\n    pyacoustics.signals.splitStereoAudio()\n\n- Split audio files on segments of silence or on pure tones::\n\n    pyacoustics.speech_detection.split_on_tone.splitFileOnTone()\n\n- Programmatically manipulate pitch or duration of a file::\n\n    pyacoustics.morph.morph_utils.praat_pitch()\n\n- Mask speech with speech shaped noise::\n\n    pyacoustics.speech_filters.speech_shaped_noise.batchMaskSpeakerData()\n\n- And more!\n\n\nMajor revisions\n================\n\nVer 1.0 (June 7, 2015)\n\n- first public release.\n\n\nFeatures as they are added\n================\n\nMask speech with speech shaped noise\n(March 21, 2016)\n\nFind syllable nuclei/estimate speech rate using Uwe Reichel's matlab code\n(July 29, 2015) \n\nFind the valley bottom between peaks (July 7th, 2015)\n\nRequirements\n================\n\nMany of the individual features require different packages.  If you aren't using those\npackages then you don't need to install the dependencies.\n\npyacoustics.intensity_and_pitch.praat_pi requires \n`praat <http://www.fon.hum.uva.nl/praat/>`_\n\npyacoustics.intensity_and_pitch.get_f0 requires the ESPS getF0 function as implemented \nby `Snack <http://www.speech.kth.se/snack/>`_ although I recall having difficulty \ninstalling it.\n\npyacoustics.speech_rate/dictionary_estimate.py requires my library \n`psyle <https://github.com/timmahrt/pysle>`_\n\npyacoustics.signals.data_fitting.py requires\n`SciPy <http://www.scipy.org/>`_,\n`NumPy <http://www.numpy.org/>`_, and\n`scikit-learn <http://scikit-learn.org/>`_\n\nMy praatIO library is used extensively and can be downloaded \n`here <https://github.com/timmahrt/praatIO>`_\n\n\nInstallation\n================\n\nIf you on Windows, you can use the installer found here (check that it is up to date though)\n`Windows installer <http://www.timmahrt.com/python_installers>`_\n\nPyAcoustics is on pypi and can be installed or upgraded from the command-line shell with pip like so::\n\n    python -m pip install pyacoustics --upgrade\n\nOtherwise, to manually install, after downloading the source from github, from a command-line shell, navigate to the directory containing setup.py and type::\n\n    python setup.py install\n\nIf python is not in your path, you'll need to enter the full path e.g.::\n\n\tC:\\Python36\\python.exe setup.py install\n\n\nExample usage\n================\n\nSee the example folders for a few real-world examples using this library.\n\n- examples/split_audio_on_silence.py\n\n    Detects the presence of speech in a recording based on acoustic \n    intensity.  Everything louder than some threshold specified by\n    the user is considered speech.\n\n- examples/split_audio_on_tone.py\n\n    Detects the presence of pure tones in a recording.  One can use\n    this to automatically segment stimuli.  Beeps can be played while\n    the speech is being recorded and then later this tool can\n    automatically segment the speech, based on the presence of those\n    tones.\n\n    Also detects speech using a pitch analysis.  Most syllables\n    contain some voicing, so a stream of modulating pitch values\n    suggests that someone is speaking.  This aspect is not extensively\n    tested but it works well for the example files.\n\n- examples/estimate_speech_rate.py\n\n    Calculates the speech rate through a matlab script written by\n    `Uwe Reichel <http://www.phonetik.uni-muenchen.de/~reichelu/>`_\n    that estimates the location of syllable boundaries.\n\n\nCiting LMEDS\n===============\n\nPyAcoustics is general purpose coding and doesn't need to be cited\nbut if you would like to, it can be cited like so:\n\nTim Mahrt. PyAcoustics. https://github.com/timmahrt/pyAcoustics, 2016.\n\n\nAcknowledgements\n================\n\nPyAcoustics is an ongoing collection of code with contributions from a\nnumber of projects worked on over several years.  Development of various\naspects of PyAcoustics was possible thanks to\nNSF grant **IIS 07-03624**\nto Jennifer Cole and Mark Hasegawa-Johnson,\nNSF grant BCS **12-51343**\nto Jennifer Cole, Jos\u00e9 Hualde, and Caroline Smith, and\nNSF grant\n**IBSS SMA 14-16791** to Jennifer Cole, Nancy McElwain, and Daniel Berry.\n\n\n",
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