Papers by Alessio Brutti

2 papers
Continual Contrastive Spoken Language Understanding (2024.findings-acl)

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Challenge: Recent advances in speech processing require extensive offline training . however, these models struggle to retain their previously acquired knowledge when learning new tasks continuously.
Approach: They propose a method that relies on experience replay and contrastive learning to preserve the learned representations by pulling closer samples from the same class and pushing away the others.
Outcome: The proposed method preserves the learned representations by pulling closer samples from the same class and pushing away the others.
MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages (2024.emnlp-main)

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Challenge: Existing speech FMs fall short of full compliance with open-source principles . existing models do not have model weights, code, and training data publicly available .
Approach: They propose to use a CC-BY license to create open-source speech FMs for EU languages . they collect suitable training data by surveying automatic speech recognition datasets .
Outcome: The proposed model can be used in the 24 official languages of the European Union.

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