activity
20162022
most citedLearning Subject-Invariant Representations from Speech-Evoked EEG Using Variational Autoencoders

21 citations · 60 across the 24 of their papers we have counts for

collaborators

31 papers

cs.CL20226 cited

Multitask Learning for Low Resource Spoken Language Understanding

Quentin Meeus, Marie-Francine Moens, Hugo Van hamme

We explore the benefits that multitask learning offer to speech processing as we train models on dual objectives with automatic speech recognition and intent classification or sent…

eess.AS2022

Weak-Supervised Dysarthria-invariant Features for Spoken Language Understanding using an FHVAE and Adversarial Training

Jinzi Qi, Hugo Van hamme

The scarcity of training data and the large speaker variation in dysarthric speech lead to poor accuracy and poor speaker generalization of spoken language understanding systems fo…

eess.AS2022

Multi-Source Transformer Architectures for Audiovisual Scene Classification

Wim Boes, Hugo Van hamme

In this technical report, the systems we submitted for subtask 1B of the DCASE 2021 challenge, regarding audiovisual scene classification, are described in detail. They are essenti…

eess.AS2022

Optimizing Temporal Resolution Of Convolutional Recurrent Neural Networks For Sound Event Detection

Wim Boes, Hugo Van hamme

In this technical report, the systems we submitted for subtask 4 of the DCASE 2021 challenge, regarding sound event detection, are described in detail. These models are closely rel…

eess.AS2022

Learning to Jointly Transcribe and Subtitle for End-to-End Spontaneous Speech Recognition

Jakob Poncelet, Hugo Van hamme

TV subtitles are a rich source of transcriptions of many types of speech, ranging from read speech in news reports to conversational and spontaneous speech in talk shows and soaps.…

eess.AS20225 cited

Pre-trained Speech Representations as Feature Extractors for Speech Quality Assessment in Online Conferencing Applications

Bastiaan Tamm, Helena Balabin, Rik Vandenberghe +1

Speech quality in online conferencing applications is typically assessed through human judgements in the form of the mean opinion score (MOS) metric. Since such a labor-intensive a…