Some of the most impactful work you can do in academia isn’t cool new algos or novel architectures. It’s data research.
Data research isn’t just dumping tokens into a json. It requires a ton of rigorous experimentation, algorithmic thinking, and actually talking to your models.
Happy to announce that Speech Robust Bench (SRB) is being presented at #ICLR2025. SRB is a comprehensive multi-lingual robustness benchmark for speech recognition.
paper: https://t.co/IDGOufnt1s
code: https://t.co/GPgfCIHZSD
data: https://t.co/EEbymoTNin
more in 🧵
@makemytripcare Absolutely worst customer service! My ticket was confirmed after boarding closed, forcing me to buy another ticket at the counter. After a week of chasing 5 different people, still no updates.
Just landed in Hyderabad for ICASSP 2025! Excited to reconnect with familiar faces and meet some new ones. Feel free to reach out or swing by the Microsoft booth for a quick chat #ICASSP2025
collaboration with @SatvikDixit9 and advised by rita singh and bhiksha raj
demo: https://t.co/65EWNVbdsQ
huggingface: https://t.co/hEEyLYfsFk
github: https://t.co/1ylRTSGG10
paper: https://t.co/ZOk7CX1xZ5
we show for the first time ever that sub-billion audio models can reason. we introduce mellow, a small audio-language model (167M) that gets SoTA on different audio reasoning tasks. by using our method and data, you can train an alm within 24 hrs on academic resources (1/n 🧵)
also, if one scales data (audio), mellow performance improves further, highlighting the effectiveness of our minimal recipe. we release the checkpoint, reasonaqa dataset, and will soon open-source the training code to make research on audio-language models more accessible!