Design Recommendations Based on Speech Analysis for Disability-Friendly Interfaces for the Control of a Home Automation Environment
Pages 197 - 211
Abstract
The objective of this paper is to describe the study on speech interaction mode for home automation control of equipment by impaired people for an inclusive housing. The study is related to the HIP HOPE project concerning a building of 19 inclusive housing units. 7 participants with different types of disabilities were invited to carry out use cases using voice and touch control. Only the results obtained on the voice interaction mode through the Amazon voice assistant are reported here. The results show, according to the type of handicap, the success rates in the speech recognition of the command emitted on the equipment and highlight the errors related to the formulation, the noisy environment, the intelligible speech, the speech segmentation and the bad synchronization of the audio channel opening.
References
[1]
Varriale L, Briganti P, and Mele S Lazazzara A, Ricciardi F, and Za S Disability and home automation: insights and challenges within organizational settings Exploring Digital Ecosystems 2020 Cham Springer 47-66
[2]
Vacher, M., et al.: Experimental evaluation of speech recognition technologies for voice-based home automation control in a smart home. In: 4th workshop on Speech and Language Processing for Assistive Technologies, 99–105 (2013). https://hal.archives-ouvertes.fr/hal-00953244
[3]
Vigouroux, N., Vella, F., Lepage, G., Campo, E.: Usability study of tactile and voice interaction modes by people with disabilities for home automation controls. In: Miesenberger, K., Kouroupetroglou, G., Mavrou, K., Manduchi, R., Covarrubias Rodriguez, M., Penáz, P. (eds.) Computers Helping People with Special Needs. ICCHP-AAATE 2022. LNCS, vol. 13342. Springer, Cham(2022).
[4]
Vacher, M., et al.: Evaluation of a context-aware voice interface for ambient assisted living: qualitative user study vs. quantitative system evaluation. ACM Trans. Access. Comput. 7, 2, Article 5, 36 p (2015).
[5]
Jefferson, M.: Usability of automatic speech recognition systems for individuals with speech disorders: Past, present, future, and a proposed model (2019)
[6]
Brewer R, Pierce C, Upadhyay P, and Park L An empirical study of older adult’s voice assistant use for health information seeking ACM Trans. Interact. Intell. Syst. 2022 12 2 1-32
[7]
Kowalski, J., et al.: Older adults and voice interaction: a pilot study with google home. In: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–6 (2019)
[8]
Alexakis G, Panagiotakis S, Fragkakis A, Markakis E, and Vassilakis K Control of smart home operations using natural language processing, voice recognition and IoT technologies in a multitier architecture Designs 2019 3 3 32
[9]
Ismail A, Abdlerazek S, and El-Henawy IM Development of smart healthcare system based on speech recognition using support vector machine and dynamic time warping Sustainability 2020 12 6 2403
[10]
Lokitha, T., Iswarya, R., Archana, A., Kumar, A., Sasikala, S.: Smart voice assistance for speech disabled and paralyzed people. In: 2022 International Conference on Computer Communication and Informatics (ICCCI), pp. 1–5. IEEE (2022)
[11]
Netinant, P., Arpabusayapan, K., Rukhiran, M.: Speech recognition for light control on raspberry pi using python programming. In: 2022 The 5th International Conference on Software Engineering and Information Management (ICSIM), pp. 33–37. IEEE (2022)
[12]
Isyanto, H., Arifin, A.S., Suryanegara, M.: Design and implementation of IoT-based smart home voice commands for disabled people using Google Assistant. In: 2020 International Conference on Smart Technology and Applications (ICoSTA), 1–6. IEEE (2020)
[13]
Yue, C.Z., Ping, S.: Voice activated smart home design and implementation. In: 2017 2nd International Conference on Frontiers of Sensors Technologies (ICFST), pp. 489–492 (2017)
[14]
Mtshali, P., Khubisa, F.: A smart home appliance control system for physically disabled people. In: 2019 Conference on Information Communications Technology and Society (ICTAS), pp. 1–5. IEEE (2019)
[15]
Malavasi, M., et al.: An innovative speech-based interface to control AAL and IoT solutions to help people with speech and motor disability. In: Cavallo, F., Marletta, V., Monteriù, A., Siciliano, P. (eds.) ForItAAL 2016. LNEE, vol. 426, pp. 269–278. Springer, Cham (2016).
[16]
van den Bossche A et al. Mokhtari M, Abdulrazak B, Aloulou H, et al. Specifying an MQTT tree for a connected smart home Smart Homes and Health Telematics, Designing a Better Future: Urban Assisted Living 2018 Cham Springer 236-246
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Published In
Jul 2023
707 pages
ISBN:978-3-031-35680-3
DOI:10.1007/978-3-031-35681-0
- Editors:
- Margherita Antona,
- Constantine Stephanidis
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 23 July 2023
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