no code implementations • SIGUL (LREC) 2022 • Phat Do, Matt Coler, Jelske Dijkstra, Esther Klabbers
ASPF was empirically confirmed to be more effective than language family as a criterion for source language selection, and also to affect the phoneme mapping’s effectiveness.
no code implementations • LREC 2022 • Martijn Bentum, Louis ten Bosch, Henk van den Heuvel, Simone Wills, Domenique van der Niet, Jelske Dijkstra, Hans Van de Velde
Adapting a speech recognizer for the council meeting domain is challenging because of acoustic background noise, speaker overlap and the jargon typically used in council meetings.
no code implementations • 21 Jun 2023 • Phat Do, Matt Coler, Jelske Dijkstra, Esther Klabbers
We compare using a PHOIBLE-based phone mapping method and using phonological features input in transfer learning for TTS in low-resource languages.
no code implementations • 1 Jun 2023 • Phat Do, Matt Coler, Jelske Dijkstra, Esther Klabbers
Results show that the G2P approach performs largely on par with using a ground-truth dictionary and the phone recognition approach, while performing generally worse, remains a viable option for LRLs less suitable for the G2P approach.
no code implementations • 30 May 2023 • Phat Do, Matt Coler, Jelske Dijkstra, Esther Klabbers
We train a MOS prediction model based on wav2vec 2. 0 using the open-access data sets BVCC and SOMOS.
no code implementations • LREC 2016 • Emre Yilmaz, Maaike Andringa, Sigrid Kingma, Jelske Dijkstra, Frits van der Kuip, Hans Van de Velde, Frederik Kampstra, Jouke Algra, Henk van den Heuvel, David van Leeuwen
Frisian is mostly spoken in the province Fryslan and it is the second official language of the Netherlands.