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Duplicate from peb-peb/shravan
Browse filesCo-authored-by: Harsh <peb-peb@users.noreply.huggingface.co>
- .gitattributes +36 -0
- .gitignore +162 -0
- CODE_OF_CONDUCT.md +66 -0
- CONTRIBUTING.md +15 -0
- LICENSE +21 -0
- README.md +14 -0
- app.py +57 -0
- data.py +24 -0
- examples/mononeg.wav +3 -0
- examples/monopos.wav +3 -0
- examples/sample4.wav +3 -0
- requirements.txt +4 -0
- sentiment_analysis.py +5 -0
- summary.py +5 -0
- topic.py +5 -0
- transcribe.py +96 -0
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.gitignore
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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gradio*
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CODE_OF_CONDUCT.md
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## Code of Conduct
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### Our Pledge
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In the interest of fostering an open and welcoming environment, we as
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contributors and maintainers pledge to making participation in our project and
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our community a harassment-free experience for everyone, regardless of age, body
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size, disability, ethnicity, gender identity and expression, level of experience,
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nationality, personal appearance, race, religion, or sexual identity and
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orientation.
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### Our Standards
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Examples of behavior that contributes to creating a positive environment
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include:
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* Using welcoming and inclusive language
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* Being respectful of differing viewpoints and experiences
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* Gracefully accepting constructive criticism
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* Focusing on what is best for the community
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* Showing empathy towards other community members
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Examples of unacceptable behavior by participants include:
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* The use of sexualized language or imagery and unwelcome sexual attention or
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advances
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* Trolling, insulting/derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or electronic
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address, without explicit permission
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* Other conduct which could reasonably be considered inappropriate in a
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professional setting
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### Our Responsibilities
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Project maintainers are responsible for clarifying the standards of acceptable
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behavior and are expected to take appropriate and fair corrective action in
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response to any instances of unacceptable behavior.
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Project maintainers have the right and responsibility to remove, edit, or
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reject comments, commits, code, wiki edits, issues, and other contributions
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that are not aligned to this Code of Conduct, or to ban temporarily or
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permanently any contributor for other behaviors that they deem inappropriate,
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threatening, offensive, or harmful.
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### Scope
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This Code of Conduct applies both within project spaces and in public spaces
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when an individual is representing the project or its community. Examples of
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representing a project or community include using an official project e-mail
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address, posting via an official social media account, or acting as an appointed
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representative at an online or offline event. Representation of a project may be
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further defined and clarified by project maintainers.
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### Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be
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reported by contacting the project team at [INSERT EMAIL ADDRESS]. All
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complaints will be reviewed and investigated and will result in a response that
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is deemed necessary and appropriate to the circumstances. The project team is
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obligated to maintain confidentiality with regard to the reporter of an incident.
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Further details of specific enforcement policies may be posted separately.
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Project maintainers who do not follow or enforce the Code of Conduct in good
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faith may face temporary or permanent repercussions as determined by other
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members of the project's leadership.
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CONTRIBUTING.md
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# Contributing
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When contributing to this repository, please first discuss the change you wish to make via issue,
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email, or any other method with the owners of this repository before making a change.
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Please note we have a code of conduct, please follow it in all your interactions with the project.
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## Pull Request Process
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1. Ensure any install or build dependencies are removed before the end of the layer when doing a
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build.
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2. Update the README.md with details of changes to the interface, this includes new environment
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variables, exposed ports, useful file locations and container parameters.
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3. You may merge the Pull Request in once you have the sign-off of two other developers, or if you
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do not have permission to do that, you may request the second reviewer to merge it for you.
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LICENSE
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MIT License
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Copyright (c) 2023 Harsh
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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title: Shravan
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emoji: 👀
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colorFrom: indigo
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colorTo: yellow
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sdk: gradio
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sdk_version: 3.35.2
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app_file: app.py
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pinned: false
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license: mit
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duplicated_from: peb-peb/shravan
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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import requests
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from transcribe import transcribe
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from sentiment_analysis import sentiment_analyser
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from summary import summarizer
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from topic import topic_gen
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def main(audio_file, number_of_speakers):
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# Audio to Text Converter
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text_data = transcribe(audio_file, number_of_speakers)
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topic = topic_gen(text_data)[0]["generated_text"]
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summary = summarizer(text_data)[0]["summary_text"]
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sent_analy = sentiment_analyser(text_data)
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sent_analysis = sent_analy[0]["label"] + " (" + str(float(sent_analy[0]["score"]) * 100) + "%)"
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return topic, summary, sent_analysis
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# UI Interface on the Hugging Face Page
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with gr.Blocks() as demo:
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gr.Markdown("""
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# Shravan - Unlocking Value from Call Data
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> **NOTE:** You need to give a `.wav` audio file and the audio file should be `monochannel`.
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""")
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with gr.Box():
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with gr.Row():
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with gr.Column():
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audio_file = gr.Audio(label="Upload an Audio file (.wav)", source="upload", type="filepath")
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number_of_speakers = gr.Number(label="Number of Speakers", value=2)
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with gr.Row():
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btn_clear = gr.ClearButton(value="Clear", components=[audio_file, number_of_speakers])
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btn_submit = gr.Button(value="Submit")
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with gr.Column():
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topic = gr.Textbox(label="Title", placeholder="Title for Conversation")
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summary = gr.Textbox(label="Short Summary", placeholder="Short Summary for Conversation")
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sentiment_analysis = gr.Textbox(label="Sentiment Analysis", placeholder="Sentiment Analysis for Conversation")
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btn_submit.click(fn=main, inputs=[audio_file, number_of_speakers], outputs=[topic, summary, sentiment_analysis])
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gr.Markdown("## Examples")
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gr.Examples(
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examples=[
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["./examples/sample4.wav", 2],
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["./examples/monopos.wav", 2],
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["./examples/mononeg.wav", 2],
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],
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inputs=[audio_file, number_of_speakers],
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outputs=[topic, summary, sentiment_analysis],
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fn=main,
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)
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gr.Markdown(
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"""
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NOTE: The Tool takes around 5mins to run. So be patient! ;)
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See [https://github.com/peb-peb/shravan](https://github.com/peb-peb/shravan) for more details.
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"""
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)
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demo.launch()
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data.py
ADDED
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data = """
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SPEAKER 1 0:00:00
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Thank you for calling Martha's Flowers. How may I assist you?
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SPEAKER 2 0:00:04
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Hello, I'd like to order flowers and I think you have what I'm looking for.
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SPEAKER 1 0:00:08
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I'd be happy to take care of your order. May I have your name please?
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SPEAKER 2 0:00:10
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Randall Thomas.
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SPEAKER 1 0:00:12
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Randall Thomas. Can you spell that for me?
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SPEAKER 2 0:00:16
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Randall, R-A-N-D-A-L-L, Thomas, T-H-O-M-A-N.
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SPEAKER 1 0:00:22
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Thank you for that information, Randall. May I have your home or office number and area code first?
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SPEAKER 2 0:00:28
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Area code 409, then 866-5088.
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SPEAKER 1 0:00:34
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That's 409-866-5088. Do you have a fax number or email address?
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SPEAKER 2 0:00:42
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My email is randall.thomas at gmail.com.
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SPEAKER 1 0:00:46
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randall.thomas at gmail.com.
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"""
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examples/mononeg.wav
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version https://git-lfs.github.com/spec/v1
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oid sha256:48ff84445d6358625065758ff2911259481b66151c054b712e752a6aa02f2f21
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size 2939982
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examples/monopos.wav
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:ebd054310c0b00ea193bc2dba688a95abccb236fd477df51fd0fd277c15748cf
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size 3787854
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examples/sample4.wav
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:839bd656f8baf785086c86ef835c7b9ad7118c6adf14bb6bdf7607a327c6129b
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size 8820078
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requirements.txt
ADDED
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git+https://github.com/pyannote/pyannote-audio
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git+https://github.com/openai/whisper.git
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git+https://github.com/huggingface/transformers
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gradio
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sentiment_analysis.py
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from transformers import pipeline
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def sentiment_analyser(text):
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sent = pipeline("sentiment-analysis",model="siebert/sentiment-roberta-large-english")
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return sent(text)
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summary.py
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from transformers import pipeline
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def summarizer(text):
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summ = pipeline("summarization", model="knkarthick/MEETING-SUMMARY-BART-LARGE-XSUM-SAMSUM-DIALOGSUM")
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return summ(text)
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topic.py
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from transformers import pipeline
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def topic_gen(text):
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topic = pipeline("text2text-generation", model="knkarthick/TOPIC-DIALOGSUM")
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return topic(text)
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transcribe.py
ADDED
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import whisper
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import datetime
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import subprocess
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import wave
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import contextlib
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import torch
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import pyannote.audio
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from pyannote.audio.pipelines.speaker_verification import PretrainedSpeakerEmbedding
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from pyannote.audio import Audio
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from pyannote.core import Segment
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from sklearn.cluster import AgglomerativeClustering
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import numpy as np
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model = whisper.load_model("large-v2")
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embedding_model = PretrainedSpeakerEmbedding(
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"speechbrain/spkrec-ecapa-voxceleb",
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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)
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def transcribe(audio, num_speakers):
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print(type(audio))
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path, error = convert_to_wav(audio)
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if error is not None:
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return error
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duration = get_duration(path)
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if duration > 4 * 60 * 60:
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return "Audio duration too long"
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result = model.transcribe(path)
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segments = result["segments"]
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num_speakers = min(max(round(num_speakers), 1), len(segments))
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if len(segments) == 1:
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segments[0]['speaker'] = 'SPEAKER 1'
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else:
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embeddings = make_embeddings(path, segments, duration)
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add_speaker_labels(segments, embeddings, num_speakers)
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output = get_output(segments)
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return output
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def convert_to_wav(path):
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if path[-3:] != 'wav':
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new_path = '.'.join(path.split('.')[:-1]) + '.wav'
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try:
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subprocess.call(['ffmpeg', '-i', path, new_path, '-y'])
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except:
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return path, 'Error: Could not convert file to .wav'
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path = new_path
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return path, None
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def get_duration(path):
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with contextlib.closing(wave.open(path,'r')) as f:
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frames = f.getnframes()
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rate = f.getframerate()
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return frames / float(rate)
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def make_embeddings(path, segments, duration):
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embeddings = np.zeros(shape=(len(segments), 192))
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for i, segment in enumerate(segments):
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embeddings[i] = segment_embedding(path, segment, duration)
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return np.nan_to_num(embeddings)
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audio = Audio()
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def segment_embedding(path, segment, duration):
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start = segment["start"]
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# Whisper overshoots the end timestamp in the last segment
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end = min(duration, segment["end"])
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clip = Segment(start, end)
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waveform, sample_rate = audio.crop(path, clip)
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return embedding_model(waveform[None])
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def add_speaker_labels(segments, embeddings, num_speakers):
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"""Add speaker labels"""
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clustering = AgglomerativeClustering(num_speakers).fit(embeddings)
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labels = clustering.labels_
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for i in range(len(segments)):
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segments[i]["speaker"] = 'SPEAKER ' + str(labels[i] + 1)
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def time(secs):
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"""Function to return time delta"""
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return datetime.timedelta(seconds=round(secs))
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def get_output(segments):
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"""Format and generate the output string"""
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output = ''
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for (i, segment) in enumerate(segments):
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if i == 0 or segments[i - 1]["speaker"] != segment["speaker"]:
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if i != 0:
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output += '\n\n'
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output += segment["speaker"] + ' ' + str(time(segment["start"])) + '\n'
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output += segment["text"][1:] + ' '
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return output
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