A CLARIN Transcription Portal for Interview Data
Christoph Draxler, Henk van den Heuvel, Arjan van Hessen, Silvia Calamai, Louise Corti
Abstract
In this paper we present a first version of a transcription portal for audio files based on automatic speech recognition (ASR) in various languages. The portal is implemented in the CLARIN resources research network and intended for use by non-technical scholars. We explain the background and interdisciplinary nature of interview data, the perks and quirks of using ASR for transcribing the audio in a research context, the dos and don’ts for optimal use of the portal, and future developments foreseen. The portal is promoted in a range of workshops, but there are a number of challenges that have to be met. These challenges concern privacy issues, ASR quality, and cost, amongst others.- Anthology ID:
- 2020.lrec-1.411
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 3353–3359
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.411
- DOI:
- Bibkey:
- Cite (ACL):
- Christoph Draxler, Henk van den Heuvel, Arjan van Hessen, Silvia Calamai, and Louise Corti. 2020. A CLARIN Transcription Portal for Interview Data. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 3353–3359, Marseille, France. European Language Resources Association.
- Cite (Informal):
- A CLARIN Transcription Portal for Interview Data (Draxler et al., LREC 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.lrec-1.411.pdf
Export citation
@inproceedings{draxler-etal-2020-clarin,
title = "A {CLARIN} Transcription Portal for Interview Data",
author = "Draxler, Christoph and
van den Heuvel, Henk and
van Hessen, Arjan and
Calamai, Silvia and
Corti, Louise",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.411",
pages = "3353--3359",
abstract = "In this paper we present a first version of a transcription portal for audio files based on automatic speech recognition (ASR) in various languages. The portal is implemented in the CLARIN resources research network and intended for use by non-technical scholars. We explain the background and interdisciplinary nature of interview data, the perks and quirks of using ASR for transcribing the audio in a research context, the dos and don{'}ts for optimal use of the portal, and future developments foreseen. The portal is promoted in a range of workshops, but there are a number of challenges that have to be met. These challenges concern privacy issues, ASR quality, and cost, amongst others.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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%0 Conference Proceedings %T A CLARIN Transcription Portal for Interview Data %A Draxler, Christoph %A van den Heuvel, Henk %A van Hessen, Arjan %A Calamai, Silvia %A Corti, Louise %Y Calzolari, Nicoletta %Y Béchet, Frédéric %Y Blache, Philippe %Y Choukri, Khalid %Y Cieri, Christopher %Y Declerck, Thierry %Y Goggi, Sara %Y Isahara, Hitoshi %Y Maegaard, Bente %Y Mariani, Joseph %Y Mazo, Hélène %Y Moreno, Asuncion %Y Odijk, Jan %Y Piperidis, Stelios %S Proceedings of the Twelfth Language Resources and Evaluation Conference %D 2020 %8 May %I European Language Resources Association %C Marseille, France %@ 979-10-95546-34-4 %G English %F draxler-etal-2020-clarin %X In this paper we present a first version of a transcription portal for audio files based on automatic speech recognition (ASR) in various languages. The portal is implemented in the CLARIN resources research network and intended for use by non-technical scholars. We explain the background and interdisciplinary nature of interview data, the perks and quirks of using ASR for transcribing the audio in a research context, the dos and don’ts for optimal use of the portal, and future developments foreseen. The portal is promoted in a range of workshops, but there are a number of challenges that have to be met. These challenges concern privacy issues, ASR quality, and cost, amongst others. %U https://aclanthology.org/2020.lrec-1.411 %P 3353-3359
Markdown (Informal)
[A CLARIN Transcription Portal for Interview Data](https://aclanthology.org/2020.lrec-1.411) (Draxler et al., LREC 2020)
- A CLARIN Transcription Portal for Interview Data (Draxler et al., LREC 2020)
ACL
- Christoph Draxler, Henk van den Heuvel, Arjan van Hessen, Silvia Calamai, and Louise Corti. 2020. A CLARIN Transcription Portal for Interview Data. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 3353–3359, Marseille, France. European Language Resources Association.