DeepSpeech
common-voice
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DeepSpeech | common-voice | |
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67 | 66 | |
24,278 | 3,247 | |
1.4% | 0.9% | |
0.0 | 10.0 | |
2 months ago | 5 days ago | |
C++ | TypeScript | |
Mozilla Public License 2.0 | Mozilla Public 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.
DeepSpeech
- Common Voice
- Ask HN: Speech to text models, are they usable yet?
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Looking to recreate a cool AI assistant project with free tools
- [DeepSpeech](https://github.com/mozilla/DeepSpeech) rather than Whisper for offline speech-to-text
I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest way to implement it using free, open-source software. Here's what he used originally, followed by some open source candidates I'm considering but would love feedback and advice before starting: Original Tools: - YoloV8 does the heavy lifting with the object detection - OpenAI Whisper handles voice - GPT-4 handles the “AI” - Google Custom Search Engine handles web browsing - MacOS/iOS handles streaming the video from my iPhone to my Mac - Python for the rest Open Source Alternatives: - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection - Replacing GPT-4 is still a challenge as I know there are some good open-source LLms like Llama 2, but I don't know how to apply this in the code perhaps in the form of api - [DeepSpeech](https://github.com/mozilla/DeepSpeech) rather than Whisper for offline speech-to-text - [Coqui TTS](https://github.com/coqui-ai/TTS) instead of Whisper for text-to-speech - Browser automation with [Selenium](https://www.selenium.dev/) instead of Google Custom Search - Stream video from phone via RTSP instead of iOS integration - Python for rest of code I'm new to working with tools like OpenCV, DeepSpeech, etc so would love any advice on the best way to replicate the original project in an open source way before I dive in. Are there any good guides or better resources out there? What are some pitfalls to avoid? Any help is much appreciated!
- Speech-to-Text in Real Time
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Linux Mint XFCE
algo assim? https://github.com/mozilla/DeepSpeech
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Are there any secure and free auto transcription software ?
If you're not afraid to get a little technical, you could take a look at mozilla/DeepSpeech (installation & usage docs here).
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Web Speech API is (still) broken on Linux circa 2023
There is a lot of TTS and SST development going on (https://github.com/mozilla/TTS; https://github.com/mozilla/DeepSpeech; https://github.com/common-voice/common-voice). That is the only way they work: Contributions from the wild.
- Deepspeech /common voice.
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Mozilla Launches Responsible AI Challenge
Mozilla did release DeepSpeech[0] and Firefox Translation[1] (the latter of which they included in Firefox, to offer client-side webpage translations.)
They definitely have fewer resources than OpenAI, and they do not produce SOTA research (their publications have plummeted to 1/year anyway[2]). So the only way for them to make progress is to seek government grants or make challenges like these.
This challenge is unlikely to be profitable for the winning team: the expected value of winnings are likely around $1K when taking into account the probability that another team gets a better rank, but ML research projects are often more expensive (recently, Alpaca spent upwards of $600 on computation alone; and of course pretraining large models is much more expensive). So the main gain will be publicity.
[0]: https://github.com/mozilla/deepspeech
[1]: https://github.com/mozilla/firefox-translations/
[2]: https://research.mozilla.org/
common-voice
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OpenAI's Whisper is another case study in Colonisation
Mozillas Common Voice Project (https://commonvoice.mozilla.org/) is creating an open dataset for many minority languages to make it easier to support them in STT systems. If you speak one of these languages please consider donating a few minutes of your voice.
- Mozilla Launching a Public Voice Dataset
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Common Voice
> it was not at all obvious to me there was some way of speeding up getting a language in the first place.
Yeah, that's the biggest failing of Common Voice in my opinion. Getting a new language up to speed could be much improved by simply adding a few links to documentation, but even the existing links are broken, which I reported in March 2022... https://github.com/common-voice/common-voice/issues/3637
> I have no interest in wasting time contributing to a UI translation I actively don't want to be subjected to
Translating the UI may still help you get other people to record, even if you don't want to use it yourself.
> I'll see if I can submit some sentences at least
If you want to go faster, there's also a project to extract sentences from Wikipedia etc. in small doses Mozilla's lawyers and Wikimedia's lawyers have agreed are fair use. I think you'd only need to define how Norwegian Bokmål separates sentences. (E.g. after a period but not if it's a common abbreviation like "etc." in the preceding sentence.)
- Practice speaking and listening of your target language on Common Voice
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Web Speech API is (still) broken on Linux circa 2023
There is a lot of TTS and SST development going on (https://github.com/mozilla/TTS; https://github.com/mozilla/DeepSpeech; https://github.com/common-voice/common-voice). That is the only way they work: Contributions from the wild.
- How do I get audio data from from native speakers for Anki?
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Web Speech API is not available in the Quest browser
Since you're interested in STT and TTS, let me just plug in Mozilla's Common Voice, a way for everyone to contribute to an open source data set for STT. You can record yourself or verify other people's recordings!
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Mozilla Common Voice - Korean Language is live - Help Build a Korean Corpus for Training AI/Navi/etc
[커먼보이스 전자우편](mailto:[email protected]) || Common Voice || Korean Language Homepage || FAQs || Speaking Aloud and Reviewing Recordings || Sentence Collector || NVidia/NeMo
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Ask HN: Open-source video transcribing software?
How can it be used for transcription?
In their website I only see an interface for either uploading audio or submitting transcriptions:
https://commonvoice.mozilla.org/es
The Github repo they mention (https://github.com/common-voice/common-voice) seems to be just that sample collection software. I do not see where I can download the software to transcribe audio.
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[D] Will continuous model development inevitably lead to data leakage and overfitting?
A practical example: in the speech community, getting good results on datasets such as TIMITwould not be revolutionary, since it's super small and very old. On the contrary, things like Common Voice (which is constantly crowd-sourced) would be much more impactful. Just my two cents :)
What are some alternatives?
Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
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)
vosk-server - WebSocket, gRPC and WebRTC speech recognition server based on Vosk and Kaldi libraries
picovoice - On-device voice assistant platform powered by deep learning
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
PaddleSpeech - Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
forced-alignment-tools - A collection of links and notes on forced alignment tools
DeepSpeech-Italian-Model - Tooling for producing Italian model (public release available) for DeepSpeech and text corpus