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Top 10 Jupyter Notebook speech-recognition Projects
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DeepLearningExamples
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
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vosk-api
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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silero-models
Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
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Speech-Backbones
This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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vid2cleantxt
Python API & command-line tool to easily transcribe speech-based video files into clean text
Project mention: Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning | news.ycombinator.com | 2023-10-02I doubt it's currently actually "the best open source text to speech", but the answer I came up with when throwing a couple of hours at the problem some months ago was "Silero" [0, 1].
Following the "standalone" guide [2], it was pretty trivial to make the model render my sample text in about 100 English "voices" (many of which were similar to each other, and in varying quality). Sampling those, I got about 10 that were pretty "good". And maybe 6 that were the "best ones" (pretty natural, not annoying to listen to).
IIRC the license was free for noncommercial use only. I'm not sure exactly "how open source" they are, but it was simple to install the dependencies and write the basic Python to try it out; I had to write a for loop to try all the voices like I wanted. I ended using something else for the project for other reasons, but this could still be fairly good backup option for some use cases IMO.
[0] https://github.com/snakers4/silero-models#text-to-speech
https://github.com/MahmoudAshraf97/whisper-diarization
This project has been alright for transcribing audio with speaker diarization. A big finicky. The OpenAI model is better than other paid products(Descript, Riverside) so I’m looking forward to trying MacWhisper.
Source: https://colab.research.google.com/github/ArthurFDLR/whisper-youtube/blob/main/whisper_youtube.ipynb
Jupyter Notebook speech-recognition related posts
- VOSK Offline Speech Recognition API
- Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning
- Working Vosk model?
- Creating a live transcript bot using Vosk Ai
- What are the aplications of rust in machine learning ?
- GitHub - MahmoudAshraf97/whisper-diarization: Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
- Magyar Youtube feliratozo v.1.1 (ingyenes colab)
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A note from our sponsor - WorkOS
workos.com | 19 Apr 2024
Index
What are some of the best open-source speech-recognition projects in Jupyter Notebook? This list will help you:
Project | Stars | |
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1 | DeepLearningExamples | 12,576 |
2 | vosk-api | 6,993 |
3 | silero-models | 4,517 |
4 | whisper-diarization | 1,949 |
5 | Speech-Backbones | 521 |
6 | whisper-youtube | 315 |
7 | soxan | 218 |
8 | vid2cleantxt | 156 |
9 | Multimodal | 8 |
10 | Bangla-Spoken-Number-Recognition | 3 |