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 • LREC 2022 • Cristian Tejedor-García, Berrie van der Molen, Henk van den Heuvel, Arjan van Hessen, Toine Pieters
The current largest open-source generic automatic speech recognition (ASR) system for Dutch, Kaldi_NL, does not include a domain-specific healthcare jargon in the lexicon.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 21 Feb 2023 • Henk van den Heuvel, Martijn Bentum, Simone Wills, Judith C. Koops
In an experimental wave respondents could choose to answer open questions via speech or keyboard.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • LREC 2020 • Maria Eskevich, Franciska de Jong, Alex K{\"o}nig, er, Darja Fi{\v{s}}er, Dieter van Uytvanck, Tero Aalto, Lars Borin, Olga Gerassimenko, Jan Hajic, Henk van den Heuvel, Neeme Kahusk, Krista Liin, Martin Matthiesen, Stelios Piperidis, Kadri Vider
CLARIN is a European Research Infrastructure providing access to digital language resources and tools from across Europe and beyond to researchers in the humanities and social sciences.
no code implementations • LREC 2020 • Henk van den Heuvel
Spoken audio data, such as interview data, is a scientific instrument used by researchers in various disciplines crossing the boundaries of social sciences and humanities.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • LREC 2020 • Henk van den Heuvel, Aleksei Kelli, Katarzyna Klessa, Satu Salaasti
Corpora of disordered speech (CDS) are costly to collect and difficult to share due to personal data protection and intellectual property (IP) issues.
no code implementations • LREC 2020 • Christoph Draxler, Henk van den Heuvel, Arjan van Hessen, Silvia Calamai, Louise Corti
In this paper we present a first version of a transcription portal for audio files based on automatic speech recognition (ASR) in various languages.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 19 Jun 2019 • Emre Yilmaz, Adem Derinel, Zhou Kun, Henk van den Heuvel, Niko Brummer, Haizhou Li, David A. van Leeuwen
This paper describes our initial efforts to build a large-scale speaker diarization (SD) and identification system on a recently digitized radio broadcast archive from the Netherlands which has more than 6500 audio tapes with 3000 hours of Frisian-Dutch speech recorded between 1950-2016.
no code implementations • 23 Oct 2018 • Emre Yilmaz, Mitchell McLaren, Henk van den Heuvel, David A. van Leeuwen
In this paper, we describe several automatic annotation approaches to enable using of a large amount of raw bilingual broadcast data for acoustic model training in a semi-supervised setting.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 28 Jul 2018 • Emre Yilmaz, Henk van den Heuvel, David A. van Leeuwen
In this paper, we describe several techniques for improving the acoustic and language model of an automatic speech recognition (ASR) system operating on code-switching (CS) speech.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
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.
no code implementations • LREC 2016 • Henk van den Heuvel, Nelleke Oostdijk
In sources used in oral history research (such as interviews with eye witnesses), passages where the degree of personal emotional involvement is found to be high can be of particular interest, as these may give insight into how historical events were experienced, and what moral dilemmas and psychological or religious struggles were encountered.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • LREC 2016 • Henk van den Heuvel, S, Eric ers, Nicoline van der Sijs
This paper describes the process of semi-automatically converting dictionaries from paper to structured text (database) and the integration of these into the CLARIN infrastructure in order to make the dictionaries accessible and retrievable for the research community.
no code implementations • LREC 2014 • Nelleke Oostdijk, Henk van den Heuvel
In the context of ongoing developments as regards the creation of a sustainable, interoperable language resource infrastructure and spreading ideas of the need for open access, not only of research publications but also of the underlying data, various issues present themselves which require that different stakeholders reconsider their positions.
no code implementations • LREC 2014 • Jetske Klatter, Roel van Hout, , Henk van den Heuvel, Paula Fikkert, Anne Baker, Jan de Jong, Frank Wijnen, S, Eric ers, Paul Trilsbeek
All data sets obtained appropriate CMDI metadata files.
no code implementations • LREC 2012 • Henk van den Heuvel, S, Eric ers, Robin Rutten, Stef Scagliola, Paula Witkamp
We present a web-based tool for retrieving and annotating audio fragments of e. g. interviews.
no code implementations • LREC 2012 • Maaske Treurniet, Orph{\'e}e De Clercq, Henk van den Heuvel, Nelleke Oostdijk
In this paper we focus on the data collection processes involved and after studying the effect of media coverage we show that especially free publicity in newspapers and on social media networks results in more contributions.