Finnish Language Speech Recognition for Dental Health Care

Seppo Enarvi

    Research output: ThesisLicenciate's thesis

    Abstract

    A significant portion of the work time of dentists and nursing staff goes to writing reports and notes. This thesis studies how automatic speech recognition could ease the work load. The primary objective was to develop and evaluate an automatic speech recognition system for dental health care that records the status of patient's dentition, as dictated by a dentist. The system accepts a restricted set of spoken commands that identify a tooth or teeth and describe their condition. The status of the teeth is stored in a database. In addition to dentition status dictation, it was surveyed how well automatic speech recognition would be suited for dictating patient treatment reports. Instead of typing reports with a keyboard, a dentist could dictate them to speech recognition software that automatically transcribes them into text. The vocabulary and grammar in such a system is, in principle, unlimited. This makes it significantly harder to obtain an accurate transcription. The status commands and the report dictation language model are Finnish. Aalto University has developed an unlimited vocabulary speech recognizer that is particularly well suited for Finnish free speech recognition, but it has previously been used mainly for research purposes. In this project we experimented with adapting the recognizer to grammar-based dictation, and real end user environments. Nearly perfect recognition accuracy was obtained for dentition status dictation. Letter error rates for the report transcription task varied between 1.3 % and 17 % depending on the speaker, with no obvious explanation for so radical inter-speaker variability. Language model for report transcription was estimated using a collection of dental reports. Including a corpus of literary Finnish did not improve the results.
    Original languageEnglish
    QualificationLicentiate's degree
    Awarding Institution
    • Aalto University
    Supervisors/Advisors
    • Oja, Erkki, Supervising Professor
    • Kurimo, Mikko, Thesis Advisor
    Publisher
    Publication statusPublished - 2012
    MoE publication typeG3 Licentiate thesis

    Keywords

    • Automatic speech recognition
    • Language modeling

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