activity
20192026
most citedCompact recurrent neural networks for acoustic event detection on low-energy low-complexity platforms

58 citations · 94 across the 38 of their papers we have counts for

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Showing 2023 · eess.ASShow all

6 papers · 2 filters

eess.AS2023

Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers

Umberto Cappellazzo, Daniele Falavigna, Alessio Brutti +1

Parameter-efficient transfer learning (PETL) methods have emerged as a solid alternative to the standard full fine-tuning approach. They only train a few extra parameters for each…

eess.AS2023★ 1 cited

Continual Contrastive Spoken Language Understanding

Umberto Cappellazzo, Enrico Fini, Muqiao Yang +3

Recently, neural networks have shown impressive progress across diverse fields, with speech processing being no exception. However, recent breakthroughs in this area require extens…

eess.AS2023★ 1 cited

Training dynamic models using early exits for automatic speech recognition on resource-constrained devices

George August Wright, Umberto Cappellazzo, Salah Zaiem +5

The ability to dynamically adjust the computational load of neural models during inference is crucial for on-device processing scenarios characterised by limited and time-varying c…

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…

eess.AS2023

Sequence-Level Knowledge Distillation for Class-Incremental End-to-End Spoken Language Understanding

Umberto Cappellazzo, Muqiao Yang, Daniele Falavigna +1

The ability to learn new concepts sequentially is a major weakness for modern neural networks, which hinders their use in non-stationary environments. Their propensity to fit the c…

eess.AS2023★ 5 cited

End-to-End Integration of Speech Separation and Voice Activity Detection for Low-Latency Diarization of Telephone Conversations

Giovanni Morrone, Samuele Cornell, Luca Serafini +3

Recent works show that speech separation guided diarization (SSGD) is an increasingly promising direction, mainly thanks to the recent progress in speech separation. It performs di…