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    "info": {
        "author": "Matt Clarkson",
        "author_email": "YOUR-EMAIL@ucl.ac.uk",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Healthcare Industry",
            "Intended Audience :: Information Technology",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Scientific/Engineering :: Medical Science Apps."
        ],
        "description": "scikit-surgeryspeech\n===============================\n\n.. image:: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech/raw/master/project-icon.png\n   :height: 128px\n   :width: 128px\n   :target: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech\n   :alt: Logo\n\n.. image:: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech/badges/master/build.svg\n   :target: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech/pipelines\n   :alt: GitLab-CI test status\n\n.. image:: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech/badges/master/coverage.svg\n    :target: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech/commits/master\n    :alt: Test coverage\n\n\n\nAuthor: Kim-Celine Kahl\n\nscikit-surgeryspeech is part of the `SNAPPY`_ software project, developed at the `Wellcome EPSRC Centre for Interventional and Surgical Sciences`_, part of `University College London (UCL)`_.\n\nscikit-surgeryspeech supports Python 3.6.\n\nscikit-surgeryspeech is a project which runs the `Python Speech Recognition API`_ in the background listening\nfor a specific command. After saying the keyword you can say different commands, which get\nconverted to QT Signals.\n\nThe speech recognition is done by the `Google Cloud API`_, you have to get the credentials to use it or change the recognition service.\n\nKeyword detection is done by the `Porcupine API`_, you have to set different paths in your environment variables to get it running, described below.\n\nPlease explore the project structure, and implement your own functionality.\n\nExample usage\n-------------\n\nTo run an example, just start\n\n::\n\n    sksurgeryspeech.py\n\nMake sure Google Cloud API is set up correctly as described in the section below.\n\nAlso you have to set all the Parameters for the Porcupine keyword detection, also described below.\n\nYou can then say the keyword depending on the Porcupine keyword file you chose and afterwards a command. The command \"quit\" exits the application.\n\nNote: each time you have already entered a command, you need to say the keyword again to trigger the listening to commands.\n\nDeveloping\n----------\n\nCloning\n^^^^^^^\n\nYou can clone the repository using the following command:\n\n::\n\n    git clone https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech\n\nIf you have problems running the application, you might need to install portaudio\n\n::\n\n    brew install portaudio\n\nSet up the Porcupine keyword detection\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nIf you are running the keyword example, you need to clone the Porcupine API\n\n::\n\n    git clone https://github.com/Picovoice/Porcupine.git\n\nThen, you have to set the following environment variables (here the paths are just relative to the Porcupine folder, set the full paths) :\n\n::\n\n    PYTHONPATH=Porcupine\\binding\\python\n    PORCUPINE_DYNAMIC_LIBRARY=Porcupine\\lib\\<your os>\\<your processor type>\\<dynamic-library-file>\n    PORCUPINE_PARAMS=Porcupine\\lib\\common\\porcupine_params.pv\n    PORCUPINE_KEYWORD=Porcupine\\resources\\keyword_files\\<your os>\\<keyword file of your choice>\n\nYou can also `generate your own keyword files`_\n\nIf you are using the speech recognition service within your own application, you have to start a background thread which calls the method to listen to the keyword over and over again.\n\nYou can find an example how to create such a thread in the sksurgeryspech_demo.py\n\nUse the Google Cloud speech recognition service\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n.. _`Google Cloud API is set up correctly`:\n\nTo use the Google Cloud speech recognition service, you need to `get the credentials`_ first. After signing up, you\nshould get a json file with your credentials. Download this file and set the environment variable\n\n::\n\n    GOOGLE_APPLICATION_CREDENTIALS\n\nTo the path of your json file. You should then be able to run the application.\n\n\nChange speech recognition service\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nTo change the speech recognition service if you don't want to use the Google Cloud API, just change the command\n\n::\n\n    words = recognizer.recognize_google_cloud(audio, credentials_json=self.credentials)\n\n(file \"voice_recognition_service.py\", method \"listen_to_command(self)\")\nto the recognition service of your choice. Currently available services are:\n\n::\n\n    recognizer.recognize_sphinx(audio)\n    recognizer.recognize_google(audio)\n    recognizer.recognize_google_cloud(audio, credentials_json=GOOGLE_CLOUD_SPEECH_CREDENTIALS)\n    recognizer.recognize_wit(audio, key=WIT_AI_KEY)\n    recognizer.recognize_bing(audio, key=BING_KEY)\n    recognizer.recognize_azure(audio, key=AZURE_SPEECH_KEY)\n    recognizer.recognize_houndify(audio, client_id=HOUNDIFY_CLIENT_ID, client_key=HOUNDIFY_CLIENT_KEY)\n    recognizer.recognize_ibm(audio, username=IBM_USERNAME, password=IBM_PASSWORD)\n\nPython development\n^^^^^^^^^^^^^^^^^^\n\nThis project uses tox. Start with a clean python environment, then do:\n\n::\n\n    pip install tox\n    tox\n\nand the commands that are run can be found in tox.ini.\n\n\nInstalling\n----------\n\nYou can pip install directly from the repository as follows:\n\n::\n\n    pip install git+https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech\n\n\n\nContributing\n^^^^^^^^^^^^\n\nPlease see the `contributing guidelines`_.\n\n\nUseful links\n^^^^^^^^^^^^\n\n* `Source code repository`_\n\n\nLicensing and copyright\n-----------------------\n\nCopyright 2019 University College London.\nscikit-surgeryspeech is released under the BSD-3 license. Please see the `license file`_ for details.\n\n\nAcknowledgements\n----------------\n\nSupported by `Wellcome`_ and `EPSRC`_.\n\n\n.. _`Wellcome EPSRC Centre for Interventional and Surgical Sciences`: http://www.ucl.ac.uk/weiss\n.. _`source code repository`: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech\n.. _`SNAPPY`: https://weisslab.cs.ucl.ac.uk/WEISS/PlatformManagement/SNAPPY/wikis/home\n.. _`University College London (UCL)`: http://www.ucl.ac.uk/\n.. _`Wellcome`: https://wellcome.ac.uk/\n.. _`EPSRC`: https://www.epsrc.ac.uk/\n.. _`contributing guidelines`: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech/blob/master/CONTRIBUTING.rst\n.. _`license file`: https://weisslab.cs.ucl.ac.uk/WEISS/SoftwareRepositories/SNAPPY/scikit-surgeryspeech/blob/master/LICENSE\n.. _`Python Speech Recognition API`: https://pypi.org/project/SpeechRecognition/\n.. _`Google Cloud API`: https://cloud.google.com/speech-to-text/\n.. _`Porcupine API`: https://github.com/Picovoice/Porcupine\n.. _`generate your own keyword files`: https://github.com/Picovoice/Porcupine/tree/master/tools/optimizer\n.. _`get the credentials`: https://console.cloud.google.com/freetrial/signup/tos?_ga=2.263649484.-1718611742.1562839990\n\n\n",
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