Open-Source Attributions

TTSAudit is built with the help of the following open-source projects. We are grateful to their authors and contributors.

SpeechBrain

Apache 2.0

Open-source speech toolkit used for speaker verification via the ECAPA-TDNN model trained on VoxCeleb.

https://github.com/speechbrain/speechbrain

Faster Whisper

MIT

CTranslate2-based reimplementation of OpenAI Whisper, used for automatic speech recognition and pace analysis.

https://github.com/SYSTRAN/faster-whisper

OpenAI Whisper

MIT

General-purpose speech recognition model. Faster Whisper is derived from this work.

https://github.com/openai/whisper

PyTorch

BSD-3-Clause

Open-source machine learning framework used as the foundation for model inference.

https://github.com/pytorch/pytorch

torchaudio

BSD-2-Clause

Audio processing library for PyTorch, used for audio loading and waveform manipulation.

https://github.com/pytorch/audio

librosa

ISC

Python library for audio and music signal analysis, used for spectral feature extraction in quality analysis.

https://github.com/librosa/librosa

NumPy

BSD-3-Clause

Fundamental package for numerical computing in Python.

https://github.com/numpy/numpy

SciPy

BSD-3-Clause

Scientific computing library used for signal processing and statistical analysis.

https://github.com/scipy/scipy

Flask

BSD-3-Clause

Lightweight WSGI web framework used for the API layer.

https://github.com/pallets/flask

Angular

MIT

Web application framework used for the TTSAudit frontend and dashboard.

https://github.com/angular/angular

Sentry SDKs

MIT

Error monitoring and performance tracking SDKs for both frontend and backend.

https://github.com/getsentry/sentry-javascript