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THEMIS-SV: Automatic classification of language disorders from speech signals

Authors Charalambos Themistocleous
Dimitrios Kokkinakis
Published in Abstracts of the 4th European Stroke Organisation Conference ​(ESOC 2018). Gothenburg, Sweden, 16-18 May, 2018.
Publication year 2018
Published at Department of Swedish
Language en
Subject categories Language Technology (Computational Linguistics)


Background and Aims: Brain injuries resulting from stroke can affect the production of speech resulting in different types of language impairments, such as aphasia. Studying these productions manually is an extremely cumbersome and time consuming process. The aim of this paper is to present THEMIS-SV: a system that enables the automatic transcription of speech signals and the segmentation of vowels and consonants in Swedish. Method: The input of the system are recordings of speech. The system processes the recordings and returns an output with three tiers: the utterance tier, the word tier, and the vowels/consonants tier. Results: The output of the system is a fast and reliable transcription and segmentation of speech, which is very close to transcriptions and segmentations performed manually. The automatic segmentation of speech enables targeted acoustic measurements, such as measurements of consonant spectra, formant frequencies of vowels, fundamental frequency, pauses, speech rate, etc. and other acoustic measurements that have been known to differentiate between the different types of language disorders. Conclusion: The method proposed here can be employed for the analysis of speech of individuals with post-stroke aphasia and other language disorders and constitutes a promising step towards a fully automated differential diagnostic tool for language disorders.

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