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研究生: 潘玫樺
Pan, Mei Hua
論文名稱: 由英語為母語者即時標註自動生成字幕來輔助跨語言溝通
Task Rebalancing: Improving Multilingual Communication with Native Speakers-Generated Highlights on Automated Transcripts
指導教授: 王浩全
Wang, Hao Chuan
山下直美
Naomi Yamashita
口試委員: 張永儒
Chang, Yung Ju
袁千雯
Yuan, Chien Wen
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 38
中文關鍵詞: 自動語音辨識跨語言溝通社交註解重點提示工具即時生成字幕
外文關鍵詞: Automated speech recognition (ASR), multilingual communication, social annotation, highlighting tools, real-time transcripts
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  • 在跨語言溝通的情境之中,人們通常使用共同語言來溝通,非該共同語言母語人士(non-native speaker, NNS)相較於母語人士(native speaker, NS),時常遇到諸如無法正確理解母語人士的涵義以及無法跟上進行中對話等問題。過往研究中雖已證實自動語音辨識字幕(automated speech recognition transcript)能有效增進非母語人士對會話內容的理解,然而自動語音辨識字幕的錯誤與延遲,以及同時聽、說、讀非母語的語言,都在在增加了非母語人士在對話中的負荷。為了減輕非母語人士的負荷,本篇論文提出在自動語音辨識字幕上增加新的訊息通道,即是讓母語人士替非母語人士在自動語音辨識字幕上標註出重點,使得非母語人士能更輕易得到自動語音辨識字幕所帶來的好處。我們進行了組內設計實驗來驗證此一新的訊息通道(標註重點)對於跨語言溝通之影響,14個包含兩個母語人士及一個非母語人士的三人小組在有/無在自動語音辨識字幕上標註重點功能的兩個不同的條件下,分別進行合作性的討論。實驗結果發現,母語人士不但自發性地去標註重點,標註重點也使得他們更專注在實驗任務中並增進了他們在實驗任務中的表現,除此之外,非母語人士在跨語言溝通所認知到的訊息清晰度以及自在程度也有顯著提升。我們發現,母語人士在自動語音辨識上標註重點,可以幫助到跨語言溝通中的雙方,並進一步探討此一研究發現對於跨語言溝通系統設計之影響。


    In multilingual communication through a common language among both native speakers (NS) and non-native speakers (NNS), NNS may encounter problems in comprehending the messages of NS or following conversations. Even though automated speech recognition (ASR) transcripts provide support to NNS, such transcripts may contain errors and impose the need to simultaneously listen and read. To reduce this burden, we propose adding another channel (i.e., highlighting) through which NS can help NNS by highlighting the critical parts of transcripts, thus making them more useful to NNS. In a laboratory study involving 14 triads (two NS and one NNS in each triad), participants engaged in collaborative discussions under two conditions: audio conferencing plus ASR transcripts with and without the highlighting function. NS showed various motivations to perform the extra task of highlighting. The highlighting efforts helped NS themselves focus on the discussion and enhanced their task performance while increasing the clarity and comfort perceived by NNS during communication. Having NS generating highlights can benefit both NS and NNS, but in different ways. We discuss the implications for research and design of multilingual collaborative work.

    Abstract i 摘要 ii Acknowledgement iii Table of Contents iv List of Figures vi List of Tables vii Chapter 1 Introduction 1 Chapter 2 Background 3 2.1. Difficulties of NNS in Multilingual Communication 3 2.2. Current Technological Support 3 2.3. Highlighting Automated Transcripts 4 2.4. Rebalancing NS/NNS Tasks with Highlighting 5 Chapter 3 Research Question and Hypotheses 7 Chapter 4 Method 9 4.1. Participants 9 4.2. Materials 11 4.2.1. Task 11 4.2.2. Survey 12 4.2.3. Answer Sheet 13 4.2.4. Interview 13 4.3. Software and Equipment 13 4.3.1. Speech Recognition Tool 13 4.3.2. Transcript Interface 13 4.4. Procedure 14 Chapter 5 Measures 15 5.1. Manipulation Checks 15 5.1.1. Language Proficiency of Group Members 15 5.1.2. Accessibility to Highlighting Function 15 5.2. Measurement of NS’ Motivation 15 5.3. Measurement of Perceptions and Experience 16 5.3.1. Workload 16 5.3.2. Group Communication Quality 16 5.4. Performance Measures 16 5.4.1. Highlighting Percentage 16 5.4.2. All Identified Commonalities 16 5.4.3. Recalled Commonalities 17 Chapter 6 Results 18 6.1. Manipulation Checks 18 6.2. Motivation of NS 18 6.3. Task Rebalancing 19 6.3.1. Workload 19 6.3.2. Recalled Commonality 20 6.4. Group Communication Quality 21 6.4.1. Group Communication Quality-Comfort 21 6.4.2. Group Communication Quality-Clarity 22 6.5. Correlations between Performance and Perceptions 23 Chapter 7 Discussion 25 7.1. Motivation of NS to Highlight 25 7.2. Rebalanced Workloads 26 7.3. How NS-generated Highlights Helped NNS 27 7.4. Correlations 29 Chapter 8 Design Implications 31 8.1. Social Annotations Shared among Group Members 31 8.2. Augmenting Multilingual Communication with Versatile Highlighting 32 8.3. Empowering NNS through Redistribution of Work 32 Chapter 9 Limitation and Future Work 34 Chapter 10 Conclusion 35 References 36

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