Product Details

Metodika pro převod strukturovaných znalostí z oboru dialektologie do strojového učení

Created: 2024

English title
Methodology for Transferring Structured Knowledge from Dialectology into Machine Learning
Type
methodology
License
optional - optional free
Authors
Šimečková Marta (CLI CAS)
Stupňánek Bronislav (CLI CAS)
Karafiát Martin, Ing., Ph.D. (DCGM FIT BUT)
Vondráková Alena, RNDr., Ph.D. (UPOL)
Voženílek Vít, prof. RNDr., CSc. (UPOL)
Nétek Rostislav, RNDr., Ph.D. (UPOL)
Keywords

dialectology, linguistics, Czech language dialects, dialect documentation, dialect research, interview method, sound archive, cataloging of recordings, recording archiving, audial data, textual data, dialectological transcription, folklore transcription, text normalization, digitization, automatic speech recognition, machine learning, thematic cartography, sound map, interdisciplinary approach

Description

The methodology addresses the preparation and utilization of dialect data in dialectology through modern Machine Learning technologies. It focuses on the processes of consolidating, standardizing, and structuring audial and textual materials, which form the foundation for developing automatic speech transcription tools. The core of the study presents procedures applicable to the digitization and normalization of textual data and it includes a detailed description of dialect documentation in the field, emphasizing various exploratory methods, including digital archiving and cataloging of recordings. The methodology connects theoretical knowledge on the collection and processing of dialect material with practical procedures that involve the deployment of Machine Learning. Emphasis is placed on an interdisciplinary approach that combines linguistic expertise with technological tools for workflow automation. The methodology also includes procedures for visualizing dialectological data using thematic cartography, leading to the creation of interactive sound dialect maps and web-based atlases. This document serves not only as a practical guide for preparing specific linguistic material but also as inspiration for other research teams, both in dialectology and in the broader integration of Machine Learning into the humanities.

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