Speech Enhancement Using Dilated Wave-U-Net: an Experimental Analysis. - Mohamed Nabih Ali; Alessio Brutti; Daniele Falavigna (FRUCT, 2020)

A Speech Enhancement Front-End for Intent Classification in Noisy Environments. - Mohamed Nabih Ali; Veronica Juliana Schmalz; Alessio Brutti; Daniele Falavigna (EUSIPCO, 2021)

Enhancing Embeddings for Speech Classification in Noisy Conditions. - Mohamed Nabih Ali; Alessio Brutti; Daniele Falavigna (INTERSPEECH, 2022)

Time-Domain Joint Training Strategies of Speech Enhancement and Intent Classification Neural Models. - Mohamed Nabih Ali; Daniele Falavigna; Alessio Brutti (Sensors, 2022)

Scaling strategies for on-device low-complexity source separation with Conv-Tasnet. - Mohamed Nabih Ali; Francesco Paissan; Daniele Falavigna; Alessio Brutti (CoRR, 2023)

Improving the Intent Classification accuracy in Noisy Environment. - Mohamed Nabih Ali; Alessio Brutti; Daniele Falavigna (CoRR, 2023)

Direct enhancement of pre-trained speech embeddings for speech processing in noisy conditions. - Mohamed Nabih Ali; Alessio Brutti; Daniele Falavigna (Comput. Speech Lang., 2023)

Training Early-Exit Architectures for Automatic Speech Recognition: Fine-Tuning Pre-Trained Models or Training from Scratch. - George August Wright; Umberto Cappellazzo; Salah Zaiem; Desh Raj; Lucas Ondel Yang; Daniele Falavigna; Mohamed Nabih Ali; Alessio Brutti (ICASSP Workshops, 2024)

Federating Dynamic Models using Early-Exit Architectures for Automatic Speech Recognition on Heterogeneous Clients. - Mohamed Nabih Ali; Alessio Brutti; Daniele Falavigna (CoRR, 2024)

EFL-PEFT: A communication Efficient Federated Learning framework using PEFT sparsification for ASR. - Mohamed Nabih Ali; Daniele Falavigna; Alessio Brutti (ICASSP, 2025)