Beyond Speech Recognition: Unveiling the Capabilities of Voice Assistants

Authors

  • Kumar. S GEMS Polytechnic College, Aurangabad
  • Ranjit Choudhary GEMS Polytechnic College, Aurangabad
  • Arpan Kumar Gupta GEMS Polytechnic College, Aurangabad
  • Prince Kumar GEMS Polytechnic College, Aurangabad
  • Amar Deep Kumar GEMS Polytechnic College, Aurangabad

DOI:

https://doi.org/10.18486/ijcsnt/13.3.186

Keywords:

Voice Assistants, Speech Recognition, Natural Language Understanding (NLU), Multi-Modal Interfaces, Task Automation, Smart Home Integration, Contextual Awareness, Language Translation, Accessibility, Third-Party Services, User Experience, Digital Companions, Technology Evolution, Conversational Interfaces, Inclusivity

Abstract

This article explores the evolutionary trajectory of voice assistants, surpassing traditional speech recognition to become versatile digital companions. With the integration of natural language understanding, multi-modal interfaces, and contextual awareness, these entities play pivotal roles in task automation, smart home integration, language translation, and accessibility, profoundly impacting user experience and daily life. As voice assistants continue to collaborate with third-party services, the article envisions an exciting future where these technologies redefine our interactions with digital assistants, shaping a new paradigm in technology evolution.

References

Kimberly L. Dahl, Cara E. Stepp, “Changes in Relative Fundamental Frequency Under Increased Cognitive Load in Individuals with Healthy Voices,” Journal of Speech, Language, and Hearing Research, vol. 64, no. 4, pp. 1189–1196, 2021. DOI: https://doi.org/10.1044/2021_JSLHR-20-00134

Bonnie Canziani, Sara MacSween, “Consumer Acceptance of Voice-Activated Smart Home Devices for Product Information Seeking and Online Ordering,” Computers in Human Behavior, vol. 119, Article 106714, 2021. doi:10.1016/j.chb.2021.106714. DOI: https://doi.org/10.1016/j.chb.2021.106714

C. Wienrich, C. Reitelbach, A. Carolus, “The Trustworthiness of Voice Assistants in the Context of Healthcare: Investigating the Effect of Perceived Expertise on the Trustworthiness of Voice Assistants, Providers, Data Receivers, and Automatic Speech Recognition,” Frontiers in Computer Science, vol. 3, Article 685250, 2021. doi:10.3389/fcomp.2021.685250. DOI: https://doi.org/10.3389/fcomp.2021.685250

Z. Zhang, “Deep Learning in Speech Recognition and Understanding,” Communications of the ACM, vol. 61, no. 11, pp. 58–65, 2018.

L. Zhu, L. Bass, G. Champlin-Scharff, “DevOps and Its Practices,” IEEE Software, vol. 33, no. 3, pp. 32–34, 2016. DOI: https://doi.org/10.1109/MS.2016.81

Velusamy Anandhan, Akilandeshwari Jeyapal, Sri Sathriyan Madhusamy, Srinath Nagaraj, Harish Bharathi Mahadevan, “Enhancing User Experience in Intelligent Voice Interfaces: Challenges, Architectural Elements, and Future Directions,” AIP Conference Proceedings, vol. 3279, Article 020019, AIP Publishing LLC, 2025. DOI: https://doi.org/10.1063/5.0261978

Downloads

Published

2024-12-31

How to Cite

Beyond Speech Recognition: Unveiling the Capabilities of Voice Assistants. (2024). International Journal of Communication Systems and Network Technologies, 13(3), 172-184. https://doi.org/10.18486/ijcsnt/13.3.186