common-voice VS DeepSpeech

Yeah there's no chance Mozilla would do anything like this:

https://commonvoice.mozilla.org/

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.

> 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.)

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.

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!

[커먼보이스 전자우편](mailto:commonvoice@mozilla.com) || Common Voice || Korean Language Homepage || FAQs || Speaking Aloud and Reviewing Recordings || Sentence Collector || NVidia/NeMo

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.

Setup: Install deepspeech with pip install deepspeech. Download pre-trained models from DeepSpeech Releases. Use a 16kHz mono WAV file.

As I understand it DeepSpeech is no longer actively maintained by Mozilla: https://github.com/mozilla/DeepSpeech/issues/3693

For Text To Speech, I've found Piper TTS useful (for situations where "quality"=="realistic"/"natual"): https://github.com/rhasspy/piper

For Speech to Text (which AIUI DeepSpeech provided), I've had some success with Vosk: https://github.com/alphacep/vosk-api

- [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!

algo assim? https://github.com/mozilla/DeepSpeech

If you're not afraid to get a little technical, you could take a look at mozilla/DeepSpeech (installation & usage docs here).