Hype or Ready for Prime Time?

Author:

Zhang Dongsong1,Chou Hsien-Ming1,Zhou Lina1

Affiliation:

1. Department of Information Systems, University of Maryland, Baltimore County, Baltimore, MD, USA

Abstract

The pervasiveness of mobile handheld devices and advancement in real-time continuous speech recognition technology has opened up a wide range of research opportunities in human-computer interaction for those devices. On the one hand, there has been an increasing amount of research on developing user-friendly speech recognition solutions and applications for mobile handheld devices. On the other hand, there are many distinct challenges in mobile speech recognition. Aiming to gain a good understanding of this emerging yet challenging area and provide a research map, this paper presents a state-of-the-art overview of this field. We will discuss three main architectures of mobile speech recognition systems, analyze their strengths and weaknesses, introduce some major research issues in the field, and highlight a number of major applications of speech recognition on handheld devices. The authors will also shed some light into important future research issues as a road map for researchers and practitioners.

Publisher

IGI Global

Subject

Computer Science Applications,History,Education

Reference37 articles.

1. A noise-robust front-end for distributed speech recognition in mobile communications

2. Cohen, J. (2008, March 31-April 4). Embedded speech recognition applications in mobile phones: status, trends, and challenges. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Las Vegas, NV (pp. 5352-5355).

3. Energy Aware Speech Recognition for Mobile Devices

4. Durling, S., & Lumsden, J. (2008, November 24-26). Speech recognition use in healthcare applications. In Proceedings of the Sixth International Conference on Advances in Mobile Computing and Multimedia, Linz, Austria (pp. 473-478).

5. Fabbrizio, G. D., Okken, T., & Wilpon, J. G. (2009, November 2-4). A speech mashup framework for multimodal mobile services. In Proceedings of the 11th International Conference on Multimodal Interfaces, Cambridge, MA (pp. 71-78).

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