speech-to-text-benchmark
vosk-api
| speech-to-text-benchmark | vosk-api | |
|---|---|---|
| 5 | 61 | |
| 655 | 12,697 | |
| 0.8% | 24.7% | |
| 4.6 | 5.2 | |
| 16 days ago | 8 days ago | |
| Python | Jupyter Notebook | |
| 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.
speech-to-text-benchmark
- 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The Mozilla DeepSpeech tests on LibreSpeech listed in your link were out of date back in 2020[1], and Coqui.ai (the continuation of Mozilla DeepSpeech) isn't even benchmarked.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...
- I got banned for using some Chinese swear words to some Chinese player and i was insta Voice banned
vosk-api
- Infini-Gram: Scaling unbounded n-gram language models to a trillion tokens
- VOSK Offline Speech Recognition API
- Apollo dev posts backend code to Git to disprove Reddit’s claims of scrapping and inefficiency
- Working Vosk model?
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Creating a live transcript bot using Vosk Ai
So I don't know if my issue comes from my lack of knowledge of discord.js/voice or VOSK. so I guess the most important thing I need to see is if I am creating a proper stream for the Vosk API to capture the audio. if I can figure out how to capture an audio stream I can probably import that in to vosk and figure out how to use vosk myself. but right now I can't even get close! Thank you in advance...Sorry if this isn't the right place for this
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What are the aplications of rust in machine learning ?
I remember a while ago checking out the issues with Vosk speech recognition (written in C). A handful of it's issues are related to segfaults and null pointers.
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Show HN: Willow – Open-Source Privacy-Focused Voice Assistant Hardware
first, good initiative! thanks for sharing. i think you gotta be more diligent and careful with the problem statement.
checking the weather in Sofia, Bulgaria requires cloud, current information. it's not "random speech". ESP SR capability issues don't mean that you cannot process it locally.
the comment was on "voice processing" i.e. sending speech to the cloud, not sending a call request to get the weather information.
besides, local intent detection, beyond 400 commands, there are great local STT options, working better than most cloud STTs for "random speech"
https://github.com/alphacep/vosk-api
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ChatGPT API is now officially available, priced at $0.002 per 1k tokens
I did a one-off text to speech tool for someone last year and had pretty good results with VOSK. One upside is that it works offline, although I imagine if you use TTS a lot you'll notice issues I didn't.
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Looking to mod a Vector with GPT-3, what are my options?
You can use vosk-api (https://github.com/alphacep/vosk-api) to listen to your audio, transform it to text, and then post the text to GPT-3, then using the vector sdk, have your responses said by vector.
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A new voice assistant that looks promising
The set up script wants to download https://github.com/alphacep/vosk-api/releases/download/v0.3.45/vosk-model-en-v0.3.45.zip, but this resource is not found. AFAICT all releases never contained a model file. Remedy: hardcode one model from https://alphacephei.com/vosk/models. I guessed and picked the one with the closest name, vosk-model-en-us-0.22.zip, just so I could continue.
What are some alternatives?
vosk-build-model - How to create your own model for vosk
whisper - Robust Speech Recognition via Large-Scale Weak Supervision
FedML - FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.
STT-examples - 🐸STT integration examples
picovoice - On-device voice assistant platform powered by deep learning