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First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @malev
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Forwarded from Spark in me (Alexander)
Russian Text Normalization for Speech Recognition

Usually no one talks about this, but STT / TTS technologies contain many "small" tasks that have to be solved, to make your STT / TTS pipeline work in real life.

For example:

- Speech recognition / dataset itself;
- Post-processing - beam-search / decoding;
- Domain customizations;
- Normalization (5 => пять);
- De-Normalization (пять => 5);

We want the Imagenet moment to arrive sooner in Speech in general.
So we released the Open STT dataset.
This time we have decided to share our text normalization to support STT research in Russian.

Please like / share / repost:

- Original publication
- Habr.com article
- GitHub repository
- Medium (coming soon!)
- Support dataset on Open Collective

#stt
#deep_learning
#nlp
Forwarded from Spark in me (Alexander)
Towards an ImageNet Moment for Speech-to-Text

First CV, and then (arguably) NLP, have had their ImageNet moment ⁠— a technical shift that makes tackling many problems much easier. Could Speech-To-Text be next?

Following the release of our production models / metrics, this is our piece on this topic on thegradient.pub! So far this is the largest work ever we have done, and I hope that it will not go under the radar.

It is in our hands now to make sure that speech recognition brings value to people worldwide, and not only some fat cats.

So, without further ado:

- The piece itself https://thegradient.pub/towards-an-imagenet-moment-for-speech-to-text/
- Some more links here https://spark-in.me/post/towards-an-imagenet-moment-for-speech-to-text
- If you are on Twitter, please repost this message - https://twitter.com/gradientpub/status/1243967773635571712

A lot of thanks to Thegradient team, especially Andrey and Jacob, for the sheer amount of work they put in to make this piece readable and understandable!

Please like, share, repost!

Also, there will be a second piece with criticism, so stay tuned!

#speech
#deep_learning