DeepSpeech
nerd-dictation
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DeepSpeech | nerd-dictation | |
---|---|---|
67 | 28 | |
24,278 | 1,158 | |
1.4% | - | |
0.0 | 3.6 | |
2 months ago | 28 days ago | |
C++ | Python | |
Mozilla Public License 2.0 | GNU General Public License v3.0 only |
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/
nerd-dictation
- why nerd-dictation support in NixOS is stuck ?
- Is anyone doing always-on voice to text with a local llama at home?
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Apollo dev posts backend code to Git to disprove Reddit’s claims of scrapping and inefficiency
nerd-dictation
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How to use notion in gnome
There's no built-in way of doing this in GNOME, but you might already get a bit further with tools like https://github.com/ideasman42/nerd-dictation
- What voice transcriber do you use?
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Disability accessibility tools for Linux such as eyetrackers and voice commands?
I'm not familiar with Talon so I don't know if this is a suitable suggestion but nerd-dictation seemed to have been well received here when it was last promoted and it looks like it's still in active development.
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Voice Control was supposed to be the Future. Is Linux lagging behind?
TBF Microsoft dropped IE, windows phone... that is not uncommon. But the OP is right, maybe not much for voice control but for dictation certainly. The FLOSS community is always far behind and thus always struggle with new technologies. We should be prepared. Since you've mentioned small open source project here's a demo of NerdDitaction. FYI Linux do have mobile devices developing.
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I've made voice input for Linux that I use instead of a keyboard and mouse
Yeah you get me. I did have RSI which was amplified by my other issue, but it was that issue that progressed and why can't type now, not RSI. I'd be interested in hearing about using numen in combination with typing, but it's likely not ideal yet. Maybe just using speech to text for some things could help? It's not my project but there's: https://github.com/ideasman42/nerd-dictation that uses the same speech recognition as numen.
- Voice to text for Linux
- nerd-dictation: Simple, hackable offline speech to text - using the VOSK-API.
What are some alternatives?
Kaldi Speech Recognition Toolkit - kaldi-asr/kaldi is the official location of the Kaldi project.
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
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)
recasepunc - Model for recasing and repunctuating ASR transcripts
picovoice - On-device voice assistant platform powered by deep learning
cursorless - Don't let the cursor slow you down
STT - 🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
TTS - 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
kaldi-active-grammar - Python Kaldi speech recognition with grammars that can be set active/inactive dynamically at decode-time
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.
monkeytype - The most customizable typing website with a minimalistic design and a ton of features. Test yourself in various modes, track your progress and improve your speed.