Do automated transcripts help non-native speakers catch up on missed conversation in audio conferences?

Hautasaari, Ari; Yamashita, Naomi

doi:10.1145/2631488.2631495

Cited by 8 publications

(2 citation statements)

References 24 publications

(39 reference statements)

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“…Significant previous work has focused on exploring tools to aid NNS in multiparty collaborations. The most widely adopted approach is to provide NNS with automated transcripts, which improves comprehension in audio and video meetings [53], and helps NNS catch up on missed conversation [31]. These approaches have both benefits and costs for NNS, because reading automated transcripts while following the ongoing conversation can create greater cognitive load.…”

Section: Challenges In Multiparty Communication Between Ns and Nnsmentioning

confidence: 99%

Increasing Native Speakers' Awareness of the Need to Slow Down in Multilingual Conversations Using a Real-Time Speech Speedometer

Duan

Yamashita²,

Fussell

2019

Proc. ACM Hum.-Comput. Interact.

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Collaborating 1 using a common language can be challenging for non-native speakers (NNS). These challenges can be reduced when native speakers (NS) adjust their speech behavior for NNS, for example by speaking more slowly. In this study, we examined whether the use of real-time speech rate feedback (a speech speedometer) would help NS monitor their speaking speed and adjust for NNS accordingly. We conducted a laboratory experiment with 20 triads of 2 NS and 1 NNS. NS in half of the groups were given the speech speedometer. We found that NS with the speech speedometer were significantly more motivated to slow down their speech but they did not actually speak more slowly, although they made other speech adjustments. Furthermore, NNS perceived the speech of NS with the speedometer less clear, and they felt less accommodated. The results highlight the need for tools that create scaffolding to help NS make speech accommodations. We conclude with some design ideas for these scaffolding tools.

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Section: Challenges In Multiparty Communication Between Ns and Nnsmentioning

confidence: 99%

Increasing Native Speakers' Awareness of the Need to Slow Down in Multilingual Conversations Using a Real-Time Speech Speedometer

Duan

Yamashita²,

Fussell

2019

Proc. ACM Hum.-Comput. Interact.

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“…According to previous research, real-time transcripts generated by ASR technologies hold the potential to facilitate the listening comprehension of NNSs [4]. ASR transcripts provide textual information that can complement audio speech and improve the comprehension of NNSs [5], [9]. Pan et al investigated how the quality of ASR transcripts impact comprehension and found that a 20% word-error-rate (WER) was the critical point for transcripts to be acceptable, and at a 10% WER, comprehension performance significantly improved compared to a no-transcript condition [4].…”

Section: Supporting Nnss' Listening Comprehension With Asr Transcriptsmentioning

confidence: 99%

Effects of Automated Transcripts on Non-Native Speakers' Listening Comprehension

Cao

Yamashita

Ishida

2018

IEICE Trans. Inf. & Syst.

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Previous research has shown that transcripts generated by automatic speech recognition (ASR) technologies can improve the listening comprehension of non-native speakers (NNSs). However, we still lack a detailed understanding of how ASR transcripts affect listening comprehension of NNSs. To explore this issue, we conducted two studies. The first study examined how the current presentation of ASR transcripts impacted NNSs' listening comprehension. 20 NNSs engaged in two listening tasks, each in different conditions: C1) audio only and C2) audio+ASR transcripts. The participants pressed a button whenever they encountered a comprehension problem, and explained each problem in the subsequent interviews. From our data analysis, we found that NNSs adopted different strategies when using the ASR transcripts; some followed the transcripts throughout the listening; some only checked them when necessary. NNSs also appeared to face difficulties following imperfect and slightly delayed transcripts while listening to speech-many reported difficulties concentrating on listening/reading or shifting between the two. The second study explored how different display methods of ASR transcripts affected NNSs' listening experiences. We focused on two display methods: 1) accuracy-oriented display which shows transcripts only after the completion of speech input analysis, and 2) speed-oriented display which shows the interim analysis results of speech input. We conducted a laboratory experiment with 22 NNSs who engaged in two listening tasks with ASR transcripts presented via the two display methods. We found that the more the NNSs paid attention to listening to the audio, the more they tended to prefer the speed-oriented transcripts, and vice versa. Mismatched transcripts were found to have negative effects on NNSs' listening comprehension. Our findings have implications for improving the presentation methods of ASR transcripts to more effectively support NNSs.

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Speakers’ Empowerment with Keywords: The Speaking Competency Development for Multilingual to Contribute in a Real-Time Interaction

Hanawa

Song

Tang

et al. 2017

Lecture Notes in Computer Science

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Do automated transcripts help non-native speakers catch up on missed conversation in audio conferences?

Cited by 8 publications

References 24 publications

Increasing Native Speakers' Awareness of the Need to Slow Down in Multilingual Conversations Using a Real-Time Speech Speedometer

Increasing Native Speakers' Awareness of the Need to Slow Down in Multilingual Conversations Using a Real-Time Speech Speedometer

Effects of Automated Transcripts on Non-Native Speakers' Listening Comprehension

Speakers’ Empowerment with Keywords: The Speaking Competency Development for Multilingual to Contribute in a Real-Time Interaction

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