Mengapa Mesin Pencari Suara Gagal Mengenali Bahasa Indonesia? Sebuah Kajian Awal Tentang ASR (Automatic Speech Recognition) Bahasa Indonesia
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Abstract
This paper is about the study of Indonesian Automatic Speech Recognition (ASR) designed by Informational- Technological Computer ( TIK). Specifically, this paper is aimed at describing how this tool operates in recognizing some in-puts in Indonesian language. TIK industry has something to do with Indonesian PWO Â where the use of the smart phones developes massively in Indonesia. This study processes around 10.774 data in Indonesian language in form of sentence, phrase, and word. From this number, less than 20% can be categorized perfect. The others have an error in format and recognition. This is due to some factors bringing about the failure of ASR in recognising the in put in Indonesian language.
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References
Adda-Decker, M., dan Lamel L. 2005. Do speech recognizers prefer female speakers Dalam Proceeding of INTERSPEECH, 2205-2208.
Dahan, D., Magnuson, J., dan Tanenhaus, M. 2001. Time course of frequency effects in spoken-word recognition: evidence from eye movements. Cognition Psychology 42, 317-367.
Fosler-Lussier, E., dan Morgan, N. 1999. Effects of speaking rate and word frequency on pronunciations in conversational speech. Speech Communication 29, 137-158.
Goldwater, S., Jurasfky, D., dan Manning, C.D. 2010. Which word are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates. Speech Communication 52, 181-200.
Jurafsky, D. dan Martin, J.H. 2008. Speech and Language Processing (2nd Edition). New York: Pearson Prentice Hall.
Luce, P., dan Pisoni, D. 1998. Recognizing spoken words: the neighborhood activation model. Ear Hearing 19, 1-36.
Shinozaki, T., dan Furui, S. 2001. Error analysis using decision trees in spontaneous presentation speech recognition. Dalam Proceeding of ASRU 2001.
Siegler, M., dan Stern, R. 1995. On the effects of speech rate in large vocabulary speech recognition systems. Dalam Proceeding of ICASSP.
Suyanto dan Adityatama, J. 2012. IndoVM: Indonesian Voice Messaging System. Proceedings of 8th International Conference on Information Science and Digital Content Technology (ICIDT), 2012, Volume 1, 145-148.
Dahan, D., Magnuson, J., dan Tanenhaus, M. 2001. Time course of frequency effects in spoken-word recognition: evidence from eye movements. Cognition Psychology 42, 317-367.
Fosler-Lussier, E., dan Morgan, N. 1999. Effects of speaking rate and word frequency on pronunciations in conversational speech. Speech Communication 29, 137-158.
Goldwater, S., Jurasfky, D., dan Manning, C.D. 2010. Which word are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates. Speech Communication 52, 181-200.
Jurafsky, D. dan Martin, J.H. 2008. Speech and Language Processing (2nd Edition). New York: Pearson Prentice Hall.
Luce, P., dan Pisoni, D. 1998. Recognizing spoken words: the neighborhood activation model. Ear Hearing 19, 1-36.
Shinozaki, T., dan Furui, S. 2001. Error analysis using decision trees in spontaneous presentation speech recognition. Dalam Proceeding of ASRU 2001.
Siegler, M., dan Stern, R. 1995. On the effects of speech rate in large vocabulary speech recognition systems. Dalam Proceeding of ICASSP.
Suyanto dan Adityatama, J. 2012. IndoVM: Indonesian Voice Messaging System. Proceedings of 8th International Conference on Information Science and Digital Content Technology (ICIDT), 2012, Volume 1, 145-148.