21 citations · 154 across the 60 of their papers we have counts for
9 papers · 1 filter
Continual Learning for Monolingual End-to-End Automatic Speech Recognition
Steven Vander Eeckt, Hugo Van hamme
Adapting Automatic Speech Recognition (ASR) models to new domains results in a deterioration of performance on the original domain(s), a phenomenon called Catastrophic Forgetting (…
A Multi-Resolution Front-End for End-to-End Speech Anti-Spoofing
Wei Liu, Meng Sun, Xiongwei Zhang +2
The choice of an optimal time-frequency resolution is usually a difficult but important step in tasks involving speech signal classification, e.g., speech anti-spoofing. The variat…
Comparison of Self-Supervised Speech Pre-Training Methods on Flemish Dutch
Jakob Poncelet, Hugo Van hamme
Recent research in speech processing exhibits a growing interest in unsupervised and self-supervised representation learning from unlabelled data to alleviate the need for large am…
Extracting Different Levels of Speech Information from EEG Using an LSTM-Based Model
Mohammad Jalilpour Monesi, Bernd Accou, Tom Francart +1
Decoding the speech signal that a person is listening to from the human brain via electroencephalography (EEG) can help us understand how our auditory system works. Linear models h…
On the long-term learning ability of LSTM LMs
Wim Boes, Robbe Van Rompaey, Lyan Verwimp +3
We inspect the long-term learning ability of Long Short-Term Memory language models (LSTM LMs) by evaluating a contextual extension based on the Continuous Bag-of-Words (CBOW) mode…
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech
Pu Wang, Bagher BabaAli, Hugo Van hamme
End-to-end (E2E) spoken language understanding (SLU) systems avoid an intermediate textual representation by mapping speech directly into intents with slot values. This approach re…
Speech Disorder Classification Using Extended Factorized Hierarchical Variational Auto-encoders
Jinzi Qi, Hugo Van hamme
Objective speech disorder classification for speakers with communication difficulty is desirable for diagnosis and administering therapy. With the current state of speech technolog…
Audiovisual transfer learning for audio tagging and sound event detection
Wim Boes, Hugo Van hamme
We study the merit of transfer learning for two sound recognition problems, i.e., audio tagging and sound event detection. Employing feature fusion, we adapt a baseline system util…
Pre-training for low resource speech-to-intent applications
Pu Wang, Hugo Van hamme
Designing a speech-to-intent (S2I) agent which maps the users' spoken commands to the agents' desired task actions can be challenging due to the diverse grammatical and lexical pre…