Mi\'{c}i Princ -- A Little Boy Teaching Speech Technologies the Chakavian Dialect

TL;DR

This paper presents a digitized Chakavian dialect version of The Little Prince, aligned at word level, to preserve cultural content and improve speech recognition models for dialectal speech processing.

Contribution

It introduces a new aligned audio-text dataset of The Little Prince in Chakavian dialect and demonstrates its use in adapting speech recognition models.

Findings

Word error rate halved with model adaptation

Character error reduced by up to two thirds

Dataset enables diverse AI and dialectal research

Abstract

This paper documents our efforts in releasing the printed and audio book of the translation of the famous novel The Little Prince into the Chakavian dialect, as a computer-readable, AI-ready dataset, with the textual and the audio components of the two releases now aligned on the level of each written and spoken word. Our motivation for working on this release is multiple. The first one is our wish to preserve the highly valuable and specific content beyond the small editions of the printed and the audio book. With the dataset published in the CLARIN.SI repository, this content is from now on at the fingertips of any interested individual. The second motivation is to make the data available for various artificial-intelligence-related usage scenarios, such as the one we follow upon inside this paper already -- adapting the Whisper-large-v3 open automatic speech recognition model, with decent performance on standard Croatian, to Chakavian dialectal speech. We can happily report that with adapting the model, the word error rate on the selected test data has being reduced to a half, while we managed to remove up to two thirds of the error on character level. We envision many more usages of this dataset beyond the set of experiments we have already performed, both on tasks of artificial intelligence research and application, as well as dialectal research. The third motivation for this release is our hope that this, now highly structured dataset, will be transformed into a digital online edition of this work, allowing individuals beyond the research and technology communities to enjoy the beauty of the message of the little boy in the desert, told through the spectacular prism of the Chakavian dialect.