Towards the Design and Evaluation of ROILA: A Speech Recognition Friendly Artificial Language

  • Omar Mubin
  • Christoph Bartneck
  • Loe Feijs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6233)

Abstract

In our research we argue for the benefits that an artificially designed language that we call ROILA could provide to improve the accuracy of speech recognition given that it is constructed on speech recognition friendly principles. We also contemplate the trade off effect of users investing some effort in learning such a language. Initially we present the design and evaluation of the vocabulary of ROILA and subsequently we describe the ROILA grammar and the method by which we rationally chose grammar rules. Our evaluation results indicated that the vocabulary of ROILA significantly outperformed English whereas we could not yet replicate similar trends while evaluating the grammar.

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References

  1. 1.
    Amir, A., Efrat, A., Srinivasan, S.: Advances in phonetic word spotting. In: The Tenth International Conference on Information and Knowledge Management, pp. 580–582. ACM Press, New York (2001)Google Scholar
  2. 2.
    Arsoy, E., Arslan, L.: A universal human machine speech interaction language for robust speech recognition applications. In: Sojka, P., Kopeček, I., Pala, K. (eds.) TSD 2004. LNCS (LNAI), vol. 3206, pp. 261–267. Springer, Heidelberg (2004)Google Scholar
  3. 3.
    Boros, M., Eckert, W., Gallwitz, F., Grz, G., Hanrieder, G., Niemann, H.: Towards understanding spontaneous speech: Word accuracy vs. concept accuracy. In: CORR (1996)Google Scholar
  4. 4.
    Carnegie-Mellon-University: Sphinx-4 (2008), http://cmusphinx.sourceforge.net/sphinx4/
  5. 5.
    David, C.: The cambridge encyclopedia of language (1997)Google Scholar
  6. 6.
    Kisa, S.E.: Toki pona - the language of good (2008), http://www.tokipona.org/
  7. 7.
    Lovitt, A., Pinto, J., Hermansky, H.: On confusions in a phoneme recognizer. IDIAP Research Report, IDIAP-RR-07-10 (2007)Google Scholar
  8. 8.
    MacLean, A., Young, R., Bellotti, V., Moran, T.: Questions, options, and criteria: Elements of design space analysis. Human-Computer Interaction 6(3), 201–250 (1991)CrossRefGoogle Scholar
  9. 9.
    Makhoul, J., Schwartz, R.: State of the art in continuous speech recognition. Proceedings of the National Academy of Sciences 92(22), 9956–9963 (1995)CrossRefGoogle Scholar
  10. 10.
    Mubin, O., Bartneck, C., Feijs, L.: Designing an artificial robotic interaction language. In: Gross, T., Gulliksen, J., Kotzé, P., Oestreicher, L., Palanque, P., Prates, R.O., Winckler, M. (eds.) INTERACT 2009. LNCS, vol. 5727, pp. 851–854. Springer, Heidelberg (2009)Google Scholar
  11. 11.
  12. 12.
    Rosenfeld, R., Olsen, D., Rudnicky, A.: Universal speech interfaces. Interactions 8(6), 34–44 (2001)CrossRefGoogle Scholar
  13. 13.
    Rudnicky, A.: Sphinx knowledge base tool (2010), http://www.speech.cs.cmu.edu/tools/lmtool-new.html
  14. 14.
    Samudravijaya, K., Barot, M.: A comparison of public-domain software tools for speech recognition. In: Workshop on Spoken Language Processing, pp. 125–131. ISCA (2003)Google Scholar
  15. 15.
    Tomko, S., Rosenfeld, R.: Speech graffiti vs. natural language: Assessing the user experience. In: Proceedings of HLT/NAACL (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Omar Mubin
    • 1
  • Christoph Bartneck
    • 1
  • Loe Feijs
    • 1
  1. 1.Department of Industrial DesignEindhoven University of TechnologyEindhovenThe Netherlands

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