Towards Age-friendly E-commerce Through Crowd-Improved Speech Recognition, Multimodal Search, and Personalized Speech Feedback

Meng, Lei; Nguyen, Quy Hy; Tian, Xinmei; Shen, Zhiqi; Chng, Eng Siong; Guan, Yunqing; Miao, Chunyan; Leung, Cyril

doi:10.1145/3126973.3129306

Cited by 7 publications

(2 citation statements)

References 25 publications

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“…For instance, research in computer vision based analysis [13] or the emergence of speech-to-text and text-to-speech services could have a big impact on user interface design guidelines. Voice commanded web applications are undoubtedly among one venue of future interests [26], which will require new guidelines. Using an additional classification based on technology in our reference model could be one way to more easily deal with such advances.…”

Section: Discussionmentioning

confidence: 99%

Towards a Reference Model of Guidelines for the Elderly Based on Technology Adoption Factors

Lindberg

Troyer

2020

Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good

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The number of older people in the EU (65 years and older) will increase to 149 million by 2050 compared to the current 101. A large percentage of this population has not followed the transition to the world of ICT. Even for application specially aimed at the elderly, the adoption is low. This suggests that despite numerous design guidelines published for designing interfaces for elderly, there is still work to be done. In this paper, we look at existing Technology Adoption Models, especially that of Lee et al. that focuses on elderly, and investigate whether current user interface design guidelines cover the adoption factors. For this, we did a literature survey on user interface design guidelines for elderly and found a rather heavy focus on the Usability factor while the others adoption factors were hardly covered. We propose to augment the set of existing user interface guidelines with guidelines that also support the other adoption facts of Lee. For this purpose, we present a first version of a reference model that could be used to organize guidelines, but also as a guide to uncover new ones. CCS CONCEPTS• Social and professional topics → Seniors; • General and reference → Design; • Human-centered computing → User centered design; Usability testing.

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Section: Discussionmentioning

confidence: 99%

Towards a Reference Model of Guidelines for the Elderly Based on Technology Adoption Factors

Lindberg

Troyer

2020

Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good

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“…Finally, we introduce a comprehensive framework to generate both spectral and prosodic features to improve the quality of generated target speaker's speech. The work has been published in [1] Multimedia Tools and Applications journal and [3].…”

Section: Contribution and Future Directionsmentioning

confidence: 99%

Voice conversion using deep neural networks

Nguyen¹

Self Cite

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This thesis focuses on techniques to improve the performance of voice conversion. Voice conversion modifies the recorded speech of a source speaker towards a given target speaker. The resultant speech is to sound like the target speaker with the language content unchanged. This technology has been applied to create personalized voice in text-to-speech or virtual avatar, speech-to-singing synthesis or spoofing attacks in speaker verification systems.

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Enhancing the Low Adoption Rate of M-commerce in Nigeria Through Yorùbá Voice Technology

Ajayi

Azeta

Misra

et al. 2021

Hybrid Intelligent Systems

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There has been claims and reports that 70% of m-commerce in Nigeria failed due to non-interactive, non-responsive and non-interesting platform. Despite the popularity and growth of m-commerce globally, developing countries like Nigeria seems to be lagging behind and at the same time, many mcommerce sites have been reported to close down due to unprofitability. The key factors that contribute to this failure are health, literacy e-literacy language and accessibility barrier.

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Towards Age-friendly E-commerce Through Crowd-Improved Speech Recognition, Multimodal Search, and Personalized Speech Feedback

Cited by 7 publications

References 25 publications

Towards a Reference Model of Guidelines for the Elderly Based on Technology Adoption Factors

Towards a Reference Model of Guidelines for the Elderly Based on Technology Adoption Factors

Voice conversion using deep neural networks

Enhancing the Low Adoption Rate of M-commerce in Nigeria Through Yorùbá Voice Technology

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