whisper-timestamped
filler-word-removal
| whisper-timestamped | filler-word-removal | |
|---|---|---|
| 2 | 1 | |
| 1,547 | 3 | |
| 7.4% | - | |
| 8.1 | 5.2 | |
| 17 days ago | 7 months ago | |
| Python | Python | |
| GNU Affero General Public License v3.0 | BSD 2-clause "Simplified" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
whisper-timestamped
-
Show HN: AI Dub Tool I Made to Watch Foreign Language Videos with My 7-Year-Old
Yes. But Whisper's word-level timings are actually quite inaccurate out of the box. There are some Python libraries that mitigate that. I tested several of them. whisper-timestamped seems to be the best one. [0]
[0] https://github.com/linto-ai/whisper-timestamped
-
AI-assisted removal of filler words from video recordings
whisper-timestamped, which is a layer on top of the Whisper set of models enabling us to get accurate word timestamps and include filler words in transcription output. This transcriber downloads the selected Whisper model to the machine running the demo and no third-party API keys are required.
filler-word-removal
-
AI-assisted removal of filler words from video recordings
In this post, I’ll explore one use case and implementation for AI-assisted post-processing that can make video presenters’ lives a little easier. We’ll go through a small demo which lets you remove disfluencies, also known as filler words, from any MP4 file. These can include words like “um”, “uh”, and similar. I will cover:
What are some alternatives?
pywhisper - openai/whisper + extra features
FFmpeg - Mirror of https://git.ffmpeg.org/ffmpeg.git
wav2vec - pure numpy implementation of wav2vec 2.0
CPython - The Python programming language
pyannote-whisper
SincNet - SincNet is a neural architecture for efficiently processing raw audio samples.
zeta - Build high-performance AI models with modular building blocks
balena - BALanced Execution through Natural Activation : a human-computer interaction methodology for code running.
speechbrain - A PyTorch-based Speech Toolkit
SpeechBird - Speech Bird is a speech recognition system which makes complete hands-free computer control truly feasible, fast and accurate. Open-Source. Based on Windows Speech Recognition (WSR) and WSR Macros.