FedML
speech-to-text-benchmark
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FedML | speech-to-text-benchmark | |
---|---|---|
6 | 5 | |
4,026 | 581 | |
1.9% | 1.5% | |
10.0 | 3.8 | |
about 14 hours ago | 3 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
FedML
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Launch HN: Flower (YC W23) – Train AI models on distributed or sensitive data
This is not new at all. There is a much stronger competitor existing in the market already: FedML (https://fedml.ai). They have a much larger open-source community, and a well-managed and widely-used MLOps (https://open.fedml.ai).
- [Discussion] How feasible is it to partition a DNN model into pieces?
speech-to-text-benchmark
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Making a Podcast Transcription Server with Express.js (source code in comments)
Even better than my experience, there's an open-source benchmark!
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DeepSpeech 60x Smaller, 9x faster, and 2x accuracy
The Mozilla DeepSpeech tests on LibreSpeech listed in your link were out of date back in 2020[1], and Coqui.ai (the continuation of Mozilla DeepSpeech) isn't even benchmarked.
https://github.com/Picovoice/speech-to-text-benchmark/issues...
What are some alternatives?
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
speechbrain - A PyTorch-based Speech Toolkit
federated-xgboost - Federated gradient boosted decision tree learning
leopard - On-device speech-to-text engine powered by deep learning
alpa - Training and serving large-scale neural networks with auto parallelization.
experta - Expert Systems for Python
DeepSpeech-Italian-Model - Tooling for producing Italian model (public release available) for DeepSpeech and text corpus
MetisFL - The first open Federated Learning framework implemented in C++ and Python.
HandyRL - HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
adaptdl - Resource-adaptive cluster scheduler for deep learning training.
nerd-dictation - Simple, hackable offline speech to text - using the VOSK-API.
hivemind - Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.