See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers

Yunhan Wu; Daniel Rough; Anna Bleakley; Justin Edwards; Orla Cooney; Philip R. Doyle; Leigh Clark; Benjamin R. Cowan

doi:10.1145/3379503.3403563

See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers

Yunhan Wu, Daniel Rough, Anna Bleakley, Justin Edwards, Orla Cooney, Philip R. Doyle, Leigh Clark, Benjamin R. Cowan

Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Limited linguistic coverage for Intelligent Personal Assistants (IPAs) means that many interact in a non-native language. Yet we know little about how IPAs currently support or hinder these users. Through native (L1) and non-native (L2) English speakers interacting with Google Assistant on a smartphone and smart speaker, we aim to understand this more deeply. Interviews revealed that L2 speakers prioritised utterance planning around perceived linguistic limitations, as opposed to L1 speakers prioritising succinctness because of system limitations. L2 speakers see IPAs as insensitive to linguistic needs resulting in failed interaction. L2 speakers clearly preferred using smartphones, as visual feedback supported diagnoses of communication breakdowns whilst allowing time to process query results. Conversely, L1 speakers preferred smart speakers, with audio feedback being seen as sufficient. We discuss the need to tailor the IPA experience for L2 users, emphasising visual feedback whilst reducing the burden of language production.

Original language	English
Title of host publication	Mobile HCI 2020
Publisher	Association for Computing Machinery (ACM)
DOIs	https://doi.org/10.1145/3379503.3403563
Publication status	Published - Oct 2020
Event	22nd International Conference on Human-Computer Interaction with Mobile Devices and Services - Duration: 5 Oct 2020 → 9 Oct 2020

Conference

Conference	22nd International Conference on Human-Computer Interaction with Mobile Devices and Services
Period	5/10/20 → 9/10/20

Keywords

speech interface
voice user interface
intelligent personal assistants
non-native speakers

Access to Document

10.1145/3379503.3403563

Link to arXiv

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Wu, Y., Rough, D., Bleakley, A., Edwards, J., Cooney, O., Doyle, P. R., Clark, L., & Cowan, B. R. (2020). See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers. In Mobile HCI 2020 Association for Computing Machinery (ACM). https://doi.org/10.1145/3379503.3403563

@inproceedings{c4e8cf70dabc4c60afe7b50d527377e2,

title = "See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers",

abstract = "Limited linguistic coverage for Intelligent Personal Assistants (IPAs) means that many interact in a non-native language. Yet we know little about how IPAs currently support or hinder these users. Through native (L1) and non-native (L2) English speakers interacting with Google Assistant on a smartphone and smart speaker, we aim to understand this more deeply. Interviews revealed that L2 speakers prioritised utterance planning around perceived linguistic limitations, as opposed to L1 speakers prioritising succinctness because of system limitations. L2 speakers see IPAs as insensitive to linguistic needs resulting in failed interaction. L2 speakers clearly preferred using smartphones, as visual feedback supported diagnoses of communication breakdowns whilst allowing time to process query results. Conversely, L1 speakers preferred smart speakers, with audio feedback being seen as sufficient. We discuss the need to tailor the IPA experience for L2 users, emphasising visual feedback whilst reducing the burden of language production.",

keywords = "speech interface, voice user interface, intelligent personal assistants, non-native speakers",

author = "Yunhan Wu and Daniel Rough and Anna Bleakley and Justin Edwards and Orla Cooney and Doyle, {Philip R.} and Leigh Clark and Cowan, {Benjamin R.}",

year = "2020",

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booktitle = "Mobile HCI 2020",

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Wu, Y, Rough, D, Bleakley, A, Edwards, J, Cooney, O, Doyle, PR, Clark, L & Cowan, BR 2020, See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers. in Mobile HCI 2020. Association for Computing Machinery (ACM), 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services, 5/10/20. https://doi.org/10.1145/3379503.3403563

See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers. / Wu, Yunhan; Rough, Daniel; Bleakley, Anna; Edwards, Justin; Cooney, Orla; Doyle, Philip R.; Clark, Leigh; Cowan, Benjamin R.

Mobile HCI 2020. Association for Computing Machinery (ACM), 2020.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers

AU - Wu, Yunhan

AU - Rough, Daniel

AU - Bleakley, Anna

AU - Edwards, Justin

AU - Cooney, Orla

AU - Doyle, Philip R.

AU - Clark, Leigh

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AB - Limited linguistic coverage for Intelligent Personal Assistants (IPAs) means that many interact in a non-native language. Yet we know little about how IPAs currently support or hinder these users. Through native (L1) and non-native (L2) English speakers interacting with Google Assistant on a smartphone and smart speaker, we aim to understand this more deeply. Interviews revealed that L2 speakers prioritised utterance planning around perceived linguistic limitations, as opposed to L1 speakers prioritising succinctness because of system limitations. L2 speakers see IPAs as insensitive to linguistic needs resulting in failed interaction. L2 speakers clearly preferred using smartphones, as visual feedback supported diagnoses of communication breakdowns whilst allowing time to process query results. Conversely, L1 speakers preferred smart speakers, with audio feedback being seen as sufficient. We discuss the need to tailor the IPA experience for L2 users, emphasising visual feedback whilst reducing the burden of language production.

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