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Converting raw transcripts into an annotated and turn-aligned TEI-XML corpus: the example of the Corpus of Serbian Forms of Address


  • Dolores Lemmenmeier-Batinić University of Zurich, Department of Slavonic Languages and Literatures, Switzerland



spoken Serbian, language biographical interviews, forms of address, data re-usability


This paper describes the procedure of building a TEI-XML corpus of spoken Serbian starting from raw transcripts. The corpus consists of semi–structured interviews, which were gathered with the aim of investigating forms of address in Serbian. The interviews were thoroughly transcribed according to GAT transcribing conventions. However, the transcription was carried out without tools that would control the validity of the GAT syntax, or align the transcript with the audio records. In order to offer this resource to a broader audience, we resolved the inconsistencies in the original transcripts, normalised the semi-orthographic transcriptions and converted the corpus into a TEI-format for transcriptions of speech. Further, we enriched the corpus by tagging and lemmatising the data. Lastly, we aligned the corpus turns to the corresponding audio segments by using a force-alignment tool. In addition to presenting the main steps involved in converting the corpus to the XML-format, this paper also discusses current challenges in the processing of spoken data, and the implications of data re-use regarding transcriptions of speech. This corpus can be used for studying Serbian from the perspective of interactional linguistics, for investigating morphosyntax, grammar, lexicon and phonetics of spoken Serbian, for studying disfluencies, as well as for testing models for automatic speech recognition and forced alignment. The corpus is freely available for research purposes.


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How to Cite

Lemmenmeier-Batinić, D. (2021). Converting raw transcripts into an annotated and turn-aligned TEI-XML corpus: the example of the Corpus of Serbian Forms of Address. Slovenščina 2.0: Empirical, Applied and Interdisciplinary Research, 9(1), 123–144.