Towards an Open-Source Dutch Speech Recognition System for the Healthcare Domain

Cristian Tejedor-García*, Berrie van der Molen, Henk van den Heuvel*, Arjan van Hessen, Toine Pieters

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
18 Downloads (Pure)

Abstract

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. Commercial alternatives (e.g., Google ASR system) are also not suitable for this purpose, not only because of the lexicon issue, but they do not safeguard privacy of sensitive data sufficiently and reliably. These reasons motivate that just a small amount of medical staff employs speech technology in the Netherlands. This paper proposes an innovative ASR training method developed within the Homo Medicinalis (HoMed) project. On the semantic level it specifically targets automatic transcription of doctor-patient consultation recordings with a focus on the use of medicines. In the first stage of HoMed, the Kaldi NL language model (LM) is fine-tuned with lists of Dutch medical terms and transcriptions of Dutch online healthcare news bulletins. Despite the acoustic challenges and linguistic complexity of the domain, we reduced the word error rate (WER) by 5.2%. The proposed method could be employed for ASR domain adaptation to other domains with sensitive and special category data. These promising results allow us to apply this methodology on highly sensitive audiovisual recordings of patient consultations at the Netherlands Institute for Health Services Research (Nivel).

Original languageEnglish
Title of host publication2022 Language Resources and Evaluation Conference, LREC 2022
EditorsNicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
PublisherEuropean Language Resources Association (ELRA)
Pages1032-1039
Number of pages8
ISBN (Electronic)9791095546726
Publication statusPublished - 2022
Event13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France
Duration: 20 Jun 202225 Jun 2022
Conference number: 13

Conference

Conference13th International Conference on Language Resources and Evaluation Conference, LREC 2022
Abbreviated titleLREC 2022
Country/TerritoryFrance
CityMarseille
Period20/06/2225/06/22

Keywords

  • domain adaptation
  • healthcare
  • language modeling
  • speech recognition

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