@gallilmaimon.bsky.social and his team trained a Speech Language Models on 1xA5000 GPU in 24 hours

I love papers that make ML training accessible with consumer GPUs. Great example: "Slamming: Training a Speech Language Model on One GPU in a Day" released 3 days ago. The full code and training data are available and reproducible using a 24GB RTX 3090.

- arxiv.org/abs/2502.15814

🚨Attention #speech @hf.co people🤗💬
We added official support for mhubert-25hz from TWIST in transformers. We also converted it from fairseq to HF!

Check it out✌️
huggingface.co/slprl/mhuber...

I am thrilled to share that SALMon🍣 got accepted to #ICASSP25

For code, data, preprint and live leaderboard checkout - pages.cs.huji.ac.il/adiyoss-lab/...

w/ Amit Roth and Yossi Adi

#Speech people: I am looking for examples (or resources) where stress or emphasis on a phrase changes the meaning of a sentence. This part of a study on intonation in SpeechLMs.

I gave a decent ChatGPT answer below, but many weren't great...

We added SpiritLM to the SALMon🍣 leaderboard! Nice jump in emotion consistency, but still no improvement in jointly modelling text content and acoustics🥲
Think your SLM can do better?💪
links👇

I've started putting together a starter pack with people working on Speech Technology and Speech Science: go.bsky.app/BQ7mbkA

(Self-)nominations welcome!