Sirvi Autor "Lehtsalu, Kevin" järgi

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Kindlustusettevõtte kõnede automaatne transkriptsioon ja sentimendi analüüs
(Tartu Ülikool, 2025) Lehtsalu, Kevin; Sirts, Kairit, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
Automatic call transcription and analysis is a rapidly developing field within natural language processing, enabling organizations to extract valuable information from unstructured audio data. This master’s thesis explores how such solutions could be applied in the insurance domain, where recorded customer calls contain important insights into client needs, service quality, and internal processes. Although tools for automatic processing exist, they have not been systematically implemented in the organization under study - the content of calls has so far been assessed manually. In the first part of the thesis, various automatic transcription models (Whisper, Kaldi, and Wav2Vec 2.0) are tested to determine which performs best for processing insurance related calls in Estonian. The models are evaluated in terms of transcription accuracy and technical applicability, taking into account the specific challenges of low resource languages, such as morphological complexity and limited training data. The second part focuses on sentiment analysis based on the transcribed texts. Both lexicon based and machine learning based methods are compared to assess their ability to detect customers emotional stance or satisfaction. Such information is valuable for improving customer experience and gathering meaningful feedback. Based on the results, the thesis provides recommendations for selecting the most suitable transcription model and assesses under which conditions automatic sentiment detection may offer added value. As a next step, the organization could consider developing a prototype based on automatic analysis to support content-based processing of call recordings and improve both service quality monitoring and data management.