Network and Embedded Applications of Automatic Speech Recognition

Authors

  • Nobuo Hataoka Tohoku Institute of Technology
  • Hiroaki Kokubo Central Research Laboratory, Hitachi Ltd
  • Akinobu Lee Nagoya Institute of Technology
  • Tatsuya Kawahara Kyoto University
  • Kiyohiro Shikano Nara Institute of Science and Technology (NAIST)

DOI:

https://doi.org/10.37936/ecti-eec.200862.171767

Keywords:

Ubiquitous Computing, Ambient Intelligence, Automatic Speech Recognition (ASR), Continuous Speech Recognition (CSR), Julius: Free CSR Software, Embedded Julius, T-Engine, Super H Microprocessor

Abstract

ASR (Automatic Speech Recognition) is one of key technologies in the upcoming Ubiquitous Computing and Ambient Intelligence. In this paper, first, the surveys on processing devices such as microprocessors and memories, and on communication infrastructure, especially wireless communication infrastructure relating to ASR are reported. Second, the embedded version of CSR (Continuous Speech Recognition) software for the mobile environmental use of ASR is reported. As the devices, RISC based microprocessors, semiconductor memories, and HDD are summarized. For the communication infrastructure, mobile communications and wireless LANs are described. Finally, implementation results of the free CSR software called Julius on the T-engineTM consisting of an SH-4A mi-croprocessor are reported.

References

[1] Mark Weiser HP: http://www.ubiq.com/ubicomp/

[2] Philips: http://www.research.philips.com/technologies/

[3] N. Hataoka, et al. Proc. of IEEE ICASSP1998, pp.II837-II840, 1998.

[4] H. Kokubo, et al., "Embedded Julius: Continuous Speech Recognition Software for Microprocessor," in appearing in Proc. of MMSP2006, Canada, Oct., 2006.

[5] N. Hataoka, et al., "Robust Speech Dialog Interface for Car Telematics Service," Proc of IEEE CCNC2004, Las Vegas, Jan., 2004.

[6] T-Engine: http://www.t-engine.org/index.html

[7] Julius HP: http://julius.sourceforge.jp/en/julius.html/

[8] A. Lee, T. Kawahara, S. Doshita, "An Efficient Two-pass Search Algorithm using Word Trellis Index," in Proc. of ICSLP, pp.1831-1834, 1998.

[9] A. Lee and T. Kawahara and K. Shikano, "Gaussian Mixture Selection using Context-Independent HMM," Proc. of IEEE ICASSP2001-1-18, 2001.

[10] K. M. Knill, et al., "Use of Gaussian Selection in Large Vocabulary Continuous Speech Recognition using HMMs," in Proc. of ICSLP, vol. 1, pp. I-470-I-473, 1996.

[11] H. Kokubo, N. Hataoka, et al.,"Real-Time Continuous Speech Recognition System on SH-4A Microprocessor," Proc. of MMSP2007, Crete, Oct., 2007.

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Published

2008-02-27

How to Cite

Hataoka, N., Kokubo, H., Lee, A., Kawahara, T., & Shikano, K. (2008). Network and Embedded Applications of Automatic Speech Recognition. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 6(2), 91–98. https://doi.org/10.37936/ecti-eec.200862.171767

Issue

Vol. 6 No. 2 (2008): Regular Issue

Section

Research Article

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