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Simon Fraser University Speech Error Database (SFUSED) Cantonese: Methods, design, and usage
1Linguistics and Cognitive Science, Simon Fraser University, Burnaby, BC, Canada.
Frontiers in Psychology
|February 9, 2024
Summary
This study details the creation of the SFUSED Cantonese database, offering a rich resource for studying Cantonese language production. The open-access data supports research on under-studied languages and spontaneous speech error collection.
Area of Science:
- Linguistics
- Psycholinguistics
- Speech Science
Background:
- Cantonese is an under-studied language, lacking comprehensive data for language production research.
- Existing speech error databases are limited in scope or accessibility.
Purpose of the Study:
- To develop SFUSED Cantonese, a linguistically rich dataset of speech errors.
- To provide a detailed methodology for creating similar databases for under-studied languages.
- To analyze the benefits and drawbacks of spontaneous speech error collection.
Main Methods:
- Collection and analysis of audio recordings of Cantonese speech errors.
- Detailed documentation of team workflows, time budgets, and data quality control.
- Explicit articulation of linguistic and processing assumptions.
Main Results:
- The creation of the SFUSED Cantonese database, a valuable resource for linguistic research.
- A comprehensive template for investigating speech errors in other under-studied languages.
- Insights into the practicalities of collecting speech error data from spontaneous speech.
Conclusions:
- The SFUSED Cantonese database is now available as an open-access resource.
- The methodology provides a replicable framework for future speech error research.
- This work highlights the importance of creating diverse linguistic datasets.
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