Slowed-Reverbed-Surround
speechbrain
| Slowed-Reverbed-Surround | speechbrain | |
|---|---|---|
| 1 | 26 | |
| 11 | 7,892 | |
| - | 2.5% | |
| 0.0 | 9.8 | |
| about 1 year ago | 5 days ago | |
| Python | Python | |
| - | Apache License 2.0 |
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Slowed-Reverbed-Surround
speechbrain
- SpeechBrain 1.0: A free and open-source AI toolkit for all things speech
- FLaNK Stack Weekly 22 January 2024
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[D] Training ASR model using SpeechBrain
You likely have a very broken sample in one of your batches. It looks like your training actually went through a few batches before it horked the error at you. A quick google shows a similar issue in the github repo: https://github.com/speechbrain/speechbrain/issues/649 .
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Whisper.cpp
https://github.com/ggerganov/whisper.cpp https://speechbrain.github.io/
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[D] What is the best open source text to speech model?
I don't know if it's the best, but Speechbrain is supposed to be state of the art.
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[D] What's stopping you from working on speech and voice?
- https://github.com/speechbrain/speechbrain
- Specific Voice recognition
- How to get high-quality, low-cost Speech-to-Text transcription?
- [D] Speech Enhancement SOTA
- Speaker diarization
What are some alternatives?
auto-editor - Auto-Editor: Effort free video editing!
espnet - End-to-End Speech Processing Toolkit
pyannote-audio - Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Resemblyzer - A python package to analyze and compare voices with deep learning
ukrainian-onnx-model - An ONNX model for speech recognition of the Ukrainian language
SincNet - SincNet is a neural architecture for efficiently processing raw audio samples.
NeMo - A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
speech-to-text-benchmark - speech to text benchmark framework
Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.
imgaug - Image augmentation for machine learning experiments.
denoiser - Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.