Evaluating auto-translation quality: a case study of YouTube

This study examines the quality of YouTube's auto-translation English-to-Chinese subtitles. The research explores 15 videos across different genres and found 84 major translation errors which could be divided into 7 categories based on the framework of the Multidimensional Quality Metrics (MQM)...

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Bibliographic Details
Main Author: Chen, Hanzhang
Other Authors: -
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/178386
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Institution: Nanyang Technological University
Language: English
Description
Summary:This study examines the quality of YouTube's auto-translation English-to-Chinese subtitles. The research explores 15 videos across different genres and found 84 major translation errors which could be divided into 7 categories based on the framework of the Multidimensional Quality Metrics (MQM) framework. Moreover, the study delves into the translation capability of Gemini and compares the errors generated by Gemini with those generated by the YouTube auto-translation system. The study finds that Gemini could significantly improve the translation quality.