most citedLow-complexity acoustic scene classification in DCASE 2022 Challenge

22 citations · 24 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2024

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…

eess.AS2023

An Experimental Review of Speaker Diarization methods with application to Two-Speaker Conversational Telephone Speech recordings

Luca Serafini, Samuele Cornell, Giovanni Morrone +3

We performed an experimental review of current diarization systems for the conversational telephone speech (CTS) domain. In detail, we considered a total of eight different algorit…

cs.CL2023

Improving the Intent Classification accuracy in Noisy Environment

Mohamed Nabih Ali, Alessio Brutti, Daniele Falavigna

Intent classification is a fundamental task in the spoken language understanding field that has recently gained the attention of the scientific community, mainly because of the fea…

cs.SD20232 cited

Scaling strategies for on-device low-complexity source separation with Conv-Tasnet

Mohamed Nabih Ali, Francesco Paissan, Daniele Falavigna +1

Recently, several very effective neural approaches for single-channel speech separation have been presented in the literature. However, due to the size and complexity of these mode…

eess.AS202222 cited

Low-complexity acoustic scene classification in DCASE 2022 Challenge

Irene Martín-Morató, Francesco Paissan, Alberto Ancilotto +5

This paper presents an analysis of the Low-Complexity Acoustic Scene Classification task in DCASE 2022 Challenge. The task was a continuation from the previous years, but the low-c…