11 papers
RT-SEMamba: Real-Time Speech Enhancement Mamba via Progressive Knowledge Distillation
Rong Chao, Sung-Feng Huang, Moreno La Quatra +4
We present RT-SEMamba, a fully causal speech enhancement (SE) model built upon causal time-frequency Mamba blocks. Unlike Transformer-based architectures that rely on a growing key…
FAME: Fictional Actors for Multilingual Erasure
Claudio Savelli, Moreno La Quatra, Alkis Koudounas +1
LLMs trained on web-scale data raise concerns about privacy and the right to be forgotten. To address these issues, Machine Unlearning provides techniques to remove specific inform…
Challenging the Abilities of Large Language Models in Italian: a Community Initiative
Malvina Nissim, Danilo Croce, Viviana Patti +78
The rapid progress of Large Language Models (LLMs) has transformed natural language processing and broadened its impact across research and society. Yet, systematic evaluation of t…
Hallucination Benchmark for Speech Foundation Models
Alkis Koudounas, Moreno La Quatra, Manuel Giollo +2
Hallucinations in automatic speech recognition (ASR) systems refer to fluent and coherent transcriptions produced by neural ASR models that are completely unrelated to the underlyi…
An Investigation of Incorporating Mamba for Speech Enhancement
Rong Chao, Wen-Huang Cheng, Moreno La Quatra +4
This work aims to investigate the use of a recently proposed, attention-free, scalable state-space model (SSM), Mamba, for the speech enhancement (SE) task. In particular, we emplo…
"KAN you hear me?" Exploring Kolmogorov-Arnold Networks for Spoken Language Understanding
Alkis Koudounas, Moreno La Quatra, Eliana Pastor +2
Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional neural architectures, yet their application to speech processing remains under exp…