DeepSpeech
STT
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DeepSpeech | STT | |
---|---|---|
67 | 11 | |
24,212 | 2,130 | |
1.2% | 2.7% | |
0.0 | 0.6 | |
2 months ago | about 1 month ago | |
C++ | C++ | |
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
STT
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Rest in Peas: The Unrecognized Death of Speech Recognition (2010)
What has happened since then? I know Common Voice has come and gone https://en.wikipedia.org/wiki/Common_Voice https://github.com/coqui-ai/STT
And I've seen some neural approaches too
No idea where to look for comparisons though.
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Numen - FOSS voice control for handsfree computing
I basically just used coqui stt https://github.com/coqui-ai/STT
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Are there any OCR and Speech-to-Text services that are privacy friendly?
This speech-to-text works well: https://github.com/coqui-ai/STT. openai's "whisper" is probably better but I haven't tried it: https://towardsdatascience.com/transcribe-audio-files-with-openais-whisper-e973ae348aa7
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Introducing Whisper
I use two SST to live-translate audio that I listen to so I can look back (in paragraph form) to see things that I or the youtube has previously said: https://github.com/coqui-ai/STT https://github.com/ratwithacompiler/OBS-captions-plugin
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You can now tether any prod Vector to Wire's Open Source Escape Pod • thedroidyouarelookingfor
I did have to install Coqui STT and go-asticoqui manually before i was able to run Chipper.
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Currently working on a custom Virtual Assistant ('Randy') to help automate things in my shed (mainly CNC equipment) and also perform basic tasks. This morning I was able to get it to publish events on my google calendar.
What do you use as STT? I have heard good things about coqui (https://github.com/coqui-ai/STT) and will use it for my Assistant-build.
- Speech to Text Best Resource
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I put together a tutorial and overview on how to use DeepSpeech to do Speech Recognition in Python
If anyone is looking for a maintained version of DeepSpeech, checkout Coqui's repositories for STT and TTS. Coqui is lead by the engineers that used to work on DeepSpeech at Mozilla.
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CoquiTTS: 🐸💬 - Open Source Text-to-Speech framework.
Link: https://github.com/coqui-ai/STT
- Mozilla Common Voice Adds 16 New Languages and 4,600 New Hours of Speech
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 - NeMo: a framework for generative AI
picovoice - On-device voice assistant platform powered by deep learning
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
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.
OBS-captions-plugin - Closed Captioning OBS plugin using Google Speech Recognition
dicio-android - Dicio assistant app for Android
flashlight - A C++ standalone library for machine learning