Vincent Renkens

According to our database, Vincent Renkens authored at least 12 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

MARRS: Multimodal Reference Resolution System.

Halim Cagri Ates, Shruti Bhargava, Site Li, Jiarui Lu, Siddhardha Maddula, Joel Ruben Antony Moniz, Anil Kumar Nalamalapu, Roman Hoang Nguyen, Melis Özyildirim, Alkesh Patel, Dhivya Piraviperumal, Vincent Renkens, Ankit Samal, Thy Tran, Bo-Hsiang Tseng, Hong Yu, Yuan Zhang, Rong Zou

CoRR, 2023

Referring to Screen Texts with Voice Assistants.

Shruti Bhargava, Anand Dhoot, Ing-Marie Jonsson, Hoang Long Nguyen, Alkesh Patel, Hong Yu, Vincent Renkens

Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023

2021

Low resource end-to-end spoken language understanding with capsule networks.

Jakob Poncelet, Vincent Renkens, Hugo Van hamme

Comput. Speech Lang., 2021

MMIU: Dataset for Visual Intent Understanding in Multimodal Assistants.

Alkesh Patel, Joel Ruben Antony Moniz, Roman Nguyen, Nick Tzou, Hadas Kotek, Vincent Renkens

CoRR, 2021

User-Initiated Repetition-Based Recovery in Multi-Utterance Dialogue Systems.

Hoang Long Nguyen, Vincent Renkens, Joris Pelemans, Srividya Pranavi Potharaju, Anil Kumar Nalamalapu, Murat Akbacak

Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

2018

State Gradients for RNN Memory Analysis.

Lyan Verwimp, Hugo Van hamme, Vincent Renkens, Patrick Wambacq

Proceedings of the Interspeech 2018, 2018

Capsule Networks for Low Resource Spoken Language Understanding.

Vincent Renkens, Hugo Van hamme

Proceedings of the Interspeech 2018, 2018

2017

Weakly Supervised Learning of Hidden Markov Models for Spoken Language Acquisition.

Vincent Renkens, Hugo Van hamme

IEEE ACM Trans. Audio Speech Lang. Process., 2017

Automatic relevance determination for nonnegative dictionary learning in the gamma-Poisson model.

Vincent Renkens, Hugo Van hamme

Signal Process., 2017

2016

Incrementally learn the relevance of words in a dictionary for spoken language acquisition.

Vincent Renkens, Vikrant Tomar, Hugo Van hamme

Proceedings of the 2016 IEEE Spoken Language Technology Workshop, 2016

2015

Mutually exclusive grounding for weakly supervised non-negative matrix factorisation.

Vincent Renkens, Hugo Van hamme

Proceedings of the INTERSPEECH 2015, 2015

2014

Acquisition of ordinal words using weakly supervised NMF.

Vincent Renkens, Steven Janssens, Bart Ons, Jort F. Gemmeke, Hugo Van hamme

Proceedings of the 2014 IEEE Spoken Language Technology Workshop, 2014