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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
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Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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A Comparative Analysis of Whisper and VoxRex on Swedish Speech DataFredriksson, Max, Ramsay Veljanovska, Elise January 2024 (has links)
With the constant development of more advanced speech recognition models, the need to determine which models are better in specific areas and for specific purposes becomes increasingly crucial. Even more so for low-resource languages such as Swedish, dependent on the progress of models for the large international languages. Lagerlöf (2022) conducted a comparative analysis between Google’s speech-to-text model and NLoS’s VoxRex B, concluding that VoxRex was the best for Swedish audio. Since then, OpenAI released their Automatic Speech Recognition model Whisper, prompting a reassessment of the preferred choice for transcribing Swedish. In this comparative analysis using data from Swedish radio news segments, Whisper performs better than VoxRex in tests on the raw output, highly affected by more proficient sentence constructions. It is not possible to conclude which model is better regarding pure word prediction. However, the results favor VoxRex, displaying a lower variability, meaning that even though Whisper can predict full text better, the decision of what model to use should be determined by the user’s needs.
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