58 citations · 94 across the 38 of their papers we have counts for
4 papers · 1 filter
MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages
Marco Gaido, Sara Papi, Luisa Bentivogli +6
The rise of foundation models (FMs), coupled with regulatory efforts addressing their risks and impacts, has sparked significant interest in open-source models. However, existing s…
Large Language Models are Strong Audio-Visual Speech Recognition Learners
Umberto Cappellazzo, Minsu Kim, Honglie Chen +5
Multimodal large language models (MLLMs) have recently become a focal point of research due to their formidable multimodal understanding capabilities. For example, in the audio and…
Federating Dynamic Models using Early-Exit Architectures for Automatic Speech Recognition on Heterogeneous Clients
Mohamed Nabih Ali, Alessio Brutti, Daniele Falavigna
Automatic speech recognition models require large amounts of speech recordings for training. However, the collection of such data often is cumbersome and leads to privacy concerns.…
Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of Adapters
Umberto Cappellazzo, Daniele Falavigna, Alessio Brutti
Mixture of Experts (MoE) architectures have recently started burgeoning due to their ability to scale model's capacity while maintaining the computational cost affordable. Furtherm…