common-voice-android VS NeMo

I'd like to give a shout-out to Common Voice Android: https://github.com/Sav22999/common-voice-android

It's a handy app for those interested in contributing to the project. You can record voices for the languages you speak and validate other user contributions. I used to be a frequent contributor about two years ago, and this app had a much more user-friendly design compared to the official website version.

Additionally, check out the official Common Voice Matrix channel: https://chat.mozilla.org/#/room/#common-voice:mozilla.org

Donate your voice: CV Project (version 2.4): This app permits you to contribute to Common Voice from your smartphone.

The app is entirely open source and available on F-Droid:

https://github.com/Sav22999/common-voice-android

https://f-droid.org/packages/org.commonvoice.saverio/

sovelluksen koodi on täällä: https://github.com/Sav22999/common-voice-android/

O código do aplicativo está aqui: https://github.com/Sav22999/common-voice-android/

O código do aplicativo está aqui: https://github.com/Sav22999/common-voice-android/

the code of the app is here: https://github.com/Sav22999/common-voice-android/

I want to show you the Common Voice Project, a project of Mozilla Foundation (Mozilla build Firefox, Thunderbird, MDN, etc.). This project powers mycroft.ai (a privacy focussed alternative to Google Home) The project name is Common Voice; its goal is to collect voices of people to create a free and open-source dataset, which you could use for various topics, like educational, AI, etc. and currently just "Big tech" have projects like this and they required many money to use their datasets. In addition, "Big tech" develop their datasets and language models just for the most spoken languages. Mozilla, instead, wants to collect ALL languages (you can add your language also if it's a less spoken one): because Mozilla doesn't get anything (any earnings!) from this project. Helping this project is very simple, you are asked to record sentences that are shown to you or you can validate recordings from other people. All your information and data are protected, in fact you can contribute anonymously (without creating a profile). u/sav22999 is maintaining the Android app "CV Project" to make it easier for people using smartphones to contribute to this dataset . The app is free and open-source, available on all major Android app stores (Google Play, F-Droid, GitHub, Huawei AppGallery and Amazon AppStore). You can download it here: https://play.google.com/store/apps/details?id=org.commonvoice.saverio the code of the app is here: https://github.com/Sav22999/common-voice-android/ -- Why am I promoting this project? I'm not paid by Mozilla, I didn't earn anything, I do this as volunteering. . You can find more information the developer of the android app here. He is a volunteer of the Italian Mozilla community: https://people.mozilla.org/p/Sav22999 You can also come join is in the subreddit for this project r/cvp

I don't test WaveRNN but from the ones that I know the best that is open source is FastPitch. And it's easy to use, here is the tutorial for voice cloning.

Nowadays... bigger repos like https://github.com/NVIDIA/NeMo are all pytorch, lots of work also published by Meta and Microsoft is all torch. I check new work on GitHub all the time and I haven't seen a Tensorflow repo in years except one.

- https://github.com/NVIDIA/NeMo

I think there's been talk to do speaker diarization with whisper-asr-webservice[0] which is also written in python and should be able to make use of goodies such as pyannote-audio, py-webrtcvad, etc.

Whisper is great but at the point we get to kludging various things together it starts to make more sense to use something like Nvidia NeMo[1] which was built with all of this in mind and more

[0] - https://github.com/ahmetoner/whisper-asr-webservice

[1] - https://github.com/NVIDIA/NeMo

[커먼보이스 전자우편](mailto:[email protected]) || Common Voice || Korean Language Homepage || FAQs || Speaking Aloud and Reviewing Recordings || Sentence Collector || NVidia/NeMo

The final security grain was added with speech-to-text anti-spoofing built on QuartzNet from the Nemo framework. This model provides a decent quality user experience and is suitable for real-time scenarios. To measure how close what the person says to what the system expects, requires calculation of the Levenshtein distance between them.

It seems that teams who have the ability to train large models are converging on a Megatron/DeepSpeed combination for the near future. Seems the HF BigScience project has its own version, Yandex builds off the DeepSpeed/Megatron example code and NeMo has started to build model extensions on top of Megatron (for example). This is where my understanding breaks down, but I do question how much incremental progress can be made if reliant on Megatron (especially in other modalities or with custom attention mechanisms). Maybe it doesn't matter at these scales.

I worked with this a bit not that long ago. For cloud services, quality of Google and Azure "neural" voices are tough to beat. Interestingly I experienced significant latency for all of the Azure services regardless of region, configuration, etc. Never dug deep enough to figure out what was going on there. Also of note, Azure will also let you run their implementation on a local container with the usual "contact us" stuff. Not sure of the terms and pricing on that.

For local, Mozilla TTS was best from a quality standpoint but the GPU inference support was a bit dicey and (possibly) not really supported at all.

For more complex and bespoke applications the Nvidia (I know, I know) NeMO toolkit [0] is very powerful but requires more effort than most to get up and running. However, it provides the ability to do very interesting things with additional training and all things speech.

In the Nvidia world there's also their Riva [1] (formerly Jarvis) solution that works with Triton [2] to build out an architecture for extremely performant and high-scale speech applications with things like model management, revision control, deployment, etc.

[0] https://github.com/NVIDIA/NeMo

[1] https://developer.nvidia.com/riva

[2] https://developer.nvidia.com/nvidia-triton-inference-server