MoSS: Unfolding Playful Imaginaries of Synthetic Voice Design through a Modular Smart Speaker
Pages 342 - 346
Abstract
In this paper we introduce the experimental prototype MoSS (Modular Smart Speaker). MoSS is a modular speech synthesis smart speaker system, and a feature-rich and capable platform that resembles and functions as an intelligent smart speaker, while featuring extended functions for advanced audio processing. MoSS is composed by a number of software and hardware components, allowing people to customize, modify and modulate its synthetic voice in real-time. Through playfully combining the different tools and parameters, MoSS facilitates an investigation of human/machine interaction with voice controlled smart home objects, with a focus on the exploration of sound and voice synthesis. We present the process leading the creation of MoSS, how it works and the preliminary results from using the device to inspire novel vocal imaginaries in synthetic voice design.
References
[1]
Alice Baird, Stina Hasse Jørgensen, Emilia Parada-Cabaleiro, Nicholas Cummings, Simone Hantke, and Björn Schüller. 2018. The Perception of Vocal Traits in Synthesized Voices: Age, Gender, and Human Likeness. Journal of the Audio Engineering Society 66, 4: 277–285.
[2]
Julia Cambre and Chinmay Kulkarni. 2019. One Voice Fits All?: Social Implications and Research Challenges of Designing Voices for Smart Devices. Proceedings of the ACM on Human-Computer Interaction 3, CSCW: 1–19.
[3]
K. R. Chowdhary. 2020. Introducing Artificial Intelligence. In Fundamentals of Artificial Intelligence. Springer India, New Delhi, 1–23. Chelsea Finn. 2018. Learning to Learn with Gradients. PhD Thesis, EECS Department, University of Berkeley.
[4]
Leigh Clark, Philip Doyle, Diego Garaialde, 2019. The State of Speech in HCI: Trends, Themes and Challenges. Interacting with Computers 31, 4: 349–371.Matthew Van Gundy, Davide Balzarotti, and Giovanni Vigna. 2007. Catch me, if you can: Evading network signatures with web-based polymorphic worms. In Proceedings of the first USENIX workshop on Offensive Technologies (WOOT ’07) . USENIX Association, Berkley, CA, Article 7, 9 pages.
[5]
Andreea Danielescu, Sharone A Horowit-Hendler, Alexandria Pabst, Kenneth Michael Stewart, Eric M Gallo, and Matthew Peter Aylett. 2023. Creating Inclusive Voices for the 21st Century: A Non-Binary Text-to-Speech for Conversational Assistants. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ACM, 1–17.
[6]
Inchan Jung, Hankyung Kim, and Youn-kyung Lim. 2021. Understanding How Users Experience the Physiological Expression of Non-humanoid Voice-based Conversational Agent in Healthcare Services. Designing Interactive Systems Conference 2021, ACM, 1433–1446.
[7]
Edward B Kang. 2022. Biometric imaginaries: Formatting voice, body, identity to data. Social Studies of Science 52, 4: 581–602.
[8]
Christine Murad, Cosmin Munteanu, Benjamin R. Cowan, and Leigh Clark. 2021. Finding a New Voice: Transitioning Designers from GUI to VUI Design. CUI 2021 - 3rd Conference on Conversational User Interfaces, ACM, 1–12.
[9]
Thao Phan. 2017. The Materiality of the Digital and the Gendered Voice of Siri. Transformations Journal 29: 11. 10.
[10]
Miguel Sicart. 2022. Playthings. Games and Culture 17, 1: 140–155.
Recommendations
Acoustical and perceptual study of voice disguise by age modification in speaker verification
highlightsWe study the effects of voice disguise on speaker verification on a corpus of 60 native Finnish speakers from acoustic and perceptual perspectives based on automatic speaker verification system performance.Acoustic analyses with statistical ...
Do smart speaker skills support diverse audiences?
AbstractSmart speakers with voice assistants like Google Home or Amazon Alexa are increasingly popular and essential in our daily lives due to their convenience of issuing voice commands. Ensuring that these voice assistants are equitable to ...
A study of voice activity detection techniques for NIST speaker recognition evaluations
Since 2008, interview-style speech has become an important part of the NIST speaker recognition evaluations (SREs). Unlike telephone speech, interview speech has lower signal-to-noise ratio, which necessitates robust voice activity detectors (VADs). ...
Comments
Information & Contributors
Information
Published In
July 2024
501 pages
ISBN:9798400706325
DOI:10.1145/3656156
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 01 July 2024
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- Independent Research Fund Denmark
Conference
DIS '24
Sponsor:
DIS '24: Designing Interactive Systems Conference
July 1 - 5, 2024
IT University of Copenhagen, Denmark
Acceptance Rates
Overall Acceptance Rate 1,158 of 4,684 submissions, 25%
Upcoming Conference
DIS '25
- Sponsor:
- sigchi
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 197Total Downloads
- Downloads (Last 12 months)197
- Downloads (Last 6 weeks)43
Reflects downloads up to 25 Feb 2025
Other Metrics
Citations
View Options
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML FormatLogin options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in