DeepSpeech VS TTS

- [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).

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.

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/

Fast or good, choose one

Mozilla's TTS is a python package installable with pip and uses cpu or gpu resources to render a choice of voices, they mostly sound natural and this is the good. https://github.com/mozilla/TTS

Mycroft's mimic3 is the default voice renderer for the Mycroft project that runs on pi hardware and sounds ok-ish, that is the fast. https://github.com/MycroftAI/mimic3

There are many others but these are the two I use according to if it needs to run on limited hardware or if the cycles fall freely from the sky.

Coqui-ai was a commercial continuation of Mozilla TTS and STT (https://github.com/mozilla/TTS).

At the time (2018-ish), it was really impressive for on-device voice synthesis (with a quality approaching the Google and Azure cloud-based voice synthesis options) and open source, so a lot of people in the FOSS community were hoping it could be used for a privacy-respecting home assistant, Linux speech synthesis that doesn't suck, etc.

After Mozilla abandoned the project, Coqui continued development and had some really impressive one-shot voice cloning, but pivoted to marketing speech synthesis for game developers. They were probably having trouble monetizing it, and it doesn't surprise me that they shut down.

An equivalent project that's still in active development and doing really well is Piper TTS (https://github.com/rhasspy/piper).

An RSS reader that integrates TTS (or TTS)

My solution would be to use a speech synthesis library, maybe eSpeak or Festival, just for ease of use; I think they each provide a library that you could use from C or C++ easily. This one from Mozilla is a more modern system with better-quality output, but it looks like it's set up to run through Python, and I haven't looked at it closely enough to see how much work it would be to get it working for you.

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.

unfortunately not yet. I need to expand the library of languages and voices. looking around, it seems only Coqui had some traction re Brazilian Portuguese: https://github.com/mozilla/TTS/issues/160. If you foresee wide adoption of the tech for this locale, hit me up with DM

I haven't used it, but there's also mozilla/TTS.

Mozilla TTS

Instead, just use Firefox's open-source TTS model: https://github.com/mozilla/TTS