DeepSpeech
common-voice
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DeepSpeech | common-voice | |
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67 | 66 | |
24,086 | 3,230 | |
1.4% | 0.3% | |
0.0 | 10.0 | |
about 1 month 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!
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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.
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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
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Browserule
Unfortunately, only Chrome supports the technology required to provide this feature (for now). Firefox is working to include it in the browser, but it is a complex feature that requires a lot of development. Mozilla (the company who developed Firefox) actually have a tool called DeepSpeech to use speech-to-text dictation without using the Internet. I don't know if it will help you, but I've done what I could :'(
- speech-to-text on Linux?
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Show HN: State-of-the-Art German Speech Recognition in 284 lines of C++
I wrote "284 lines of C++" to indicate that this is compact enough for people to actually read and understand the source code. Also, compiling my implementation is super easy and straightforward ... something which can't be said for Kaldi, Vosk, or DeepSpeech.
If you try to read the CTC beam search decoder from Mozilla's DeepSpeech [1], that alone is about 2000 LOC in multiple files.
If you try to read the pyctcdecode source that is used by HuggingFace [2], that's 1000+ LOC of Python.
But this implementation is all the client-side, i.e. the entire "native_client" folder hierarchy in DeepSpeech [3], narrowed down to a mere 284 lines.
[1] https://github.com/mozilla/DeepSpeech/tree/master/native_cli...
[2] https://github.com/kensho-technologies/pyctcdecode
[3] https://github.com/mozilla/DeepSpeech/tree/master/native_cli...
common-voice
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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.)
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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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Common Voice dataset tops 20,000 hours
Mozilla’s Common Voice seeks to change the language technology ecosystem by supporting communities to collect voice data for the creation of voice-enabled applications for their own languages.
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Crowdsource by Google
One of the tasks in this app is audio validation:
> Audio validation: Listen to a short audio clip and determine if the pronunciation sounds natural in your language.
If this is something you're interested in doing, I recommend contributing to Mozilla's Common Voice instead. Common Voice builds freely licensed (CC-0) voice datasets that can be used by everyone, not just Google.
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Speech-To-Text Transcription
Mozilla saw that speech-to-text was dominated by proprietary implementation because you need a massive database of voice samples to train a good AI, and only the likes of Siri, Alexa and OK-Google have millions upon millions of voice samples from recording all the voice commands from their users. And they aren't sharing. So Mozilla pulled a Mozilla. Simply asked the world to donate their voice on https://commonvoice.mozilla.org, and they used the database to train an AI.
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We’re researchers from the Mozilla Foundation. We spent almost 1000 hours researching the privacy and security of this year’s most popular connected gifts to find out which ones are creepy and which ones aren’t. Ask us anything!
Hmmm...interesting question. Also, I’m sorry to your brother’s wife because that sounds super annoying. And we’re not sure it’s really effective. Just because your brother asks Alexa to turn the lights on in funny ways, Alexa still knows that their lights are being turned on. And this could also help train Amazon’s Alexa AI to understand different voices and accents and sayings (check out our Common Voice project here). Unfortunately, there’s just not much transparency in AI these days to know of ways to help protect your privacy, as far as we can tell.
What are some alternatives?
Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.
NeMo - NeMo: a framework for generative AI
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.
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
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.
dicio-android - Dicio assistant app for Android
rhasspy-mobile-app - A simple mobile app for rhasspy.
vosk-server - WebSocket, gRPC and WebRTC speech recognition server based on Vosk and Kaldi libraries
Porcupine - On-device wake word detection powered by deep learning
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple