Phonetics and Speech Sciences (말소리와 음성과학)

Korean Society of Speech Sciences (한국음성학회)
권호 표지
DOI QR코드

DOI QR Code

Google speech recognition of an English paragraph produced by college students in clear or casual speech styles

대학생들이 또렷한 음성과 대화체로 발화한 영어문단의 구글음성인식

  • Received : 2017.11.01
  • Accepted : 2017.12.18
  • Published : 2017.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

These days voice models of speech recognition software are sophisticated enough to process the natural speech of people without any previous training. However, not much research has reported on the use of speech recognition tools in the field of pronunciation education. This paper examined Google speech recognition of a short English paragraph produced by Korean college students in clear and casual speech styles in order to diagnose and resolve students' pronunciation problems. Thirty three Korean college students participated in the recording of the English paragraph. The Google soundwriter was employed to collect data on the word recognition rates of the paragraph. Results showed that the total word recognition rate was 73% with a standard deviation of 11.5%. The word recognition rate of clear speech was around 77.3% while that of casual speech amounted to 68.7%. The reasons for the low recognition rate of casual speech were attributed to both individual pronunciation errors and the software itself as shown in its fricative recognition. Various distributions of unrecognized words were observed depending on each participant and proficiency groups. From the results, the author concludes that the speech recognition software is useful to diagnose each individual or group's pronunciation problems. Further studies on progressive improvements of learners' erroneous pronunciations would be desirable.

Keywords

References

  1. Boersma, P., & Weenink, D. (2017). Praat: Doing phonetics by computer. Retrieved from http://www.fon.hum.uva.nl/praat/ on October 2, 2017.
  2. Crystal, D. (1992). An encyclopedic dictionary of language and languages. Middlesex, U.K.: Blackwell.
  3. Fowler, C., & Housum, J. (1987). Talkers' signalling of "new" and "old" words in speech and listeners' perception and use of the distinction. Journal of Memory and Language, 26, 489-504. https://doi.org/10.1016/0749-596X(87)90136-7
  4. Fromkin, V., & Rodman, R. (2013). An introduction to language. Belmont, CA: Wadsworth.
  5. Jusczyk, P., Luce, P., & Charles-Luce, J. (1994). Infants' sensitivity to phonotactic patterns in the native language. Journal of Memory & Language, 33, 630-645. https://doi.org/10.1006/jmla.1994.1030
  6. Kent, R., & Read, C. (2002). Acoustic analysis of speech. San Diego, CA: Singular Publishing Group.
  7. Lindblom, B. (1990). Explaining phonetic variation: A sketch of the H-H theory. In W. Hardcastle, & A. Marchal (Eds.), Speech production and speech modelling (pp. 403-439). London: Kluwer Academic Press.
  8. Luce, P., & Pisoni, D. (1998). Recognizing spoken words: The neighborhood activation model. Ear & Hearing, 19, 1-36. https://doi.org/10.1097/00003446-199802000-00001
  9. Pickett, J. (1987). The sounds of speech communication: A primer of acoustic phonetics and speech perception. Austin, Texas: pro-ed.
  10. R. Core Team. (2017). R: A language and environment for statistical computing. Retrieved from https://www.r-project.org/ [R Foundation for Statistical Computing, Vienna, Austria] on October 1, 2017.
  11. Vitevitch, M., & Luce, P. (2004). A web-based interface to calculate phonotactic probability for words and nonwords in English. Behavior Research Methods, Instruments, & Computers, 36(3), 481-487. https://doi.org/10.3758/BF03195594
  12. Wright, R. (2003). Factors of lexical competition in vowel articulation. In J. Local, R. Ogden, & R. Temple (Eds.), Papers in laboratory phonology VI (pp. 75-87). Cambridge: Cambridge University Press.
  13. Yang, B. (2012). Pitch and formant trajectories of English vowels by American males with different speaking styles. Phonetics and Speech Sciences, 4(1), 21-28. (양병곤 (2012). 발화방식에 따른 미국인 남성 영어모음의 피치와 포먼트 궤적. 말소리와 음성과학, 4(1), 21-28.) https://doi.org/10.13064/KSSS.2012.4.1.021
  14. Yang, B. (2014). Spectral characteristics and formant bandwidths of English vowels by American males with different speaking styles. Phonetics and Speech Sciences, 6(4), 91-99. (양병곤 (2014). 발화방식에 따른 미국인 남성 영어모음의 스펙트럼 특성과 포먼트 대역. 말소리와 음성과학, 6(4), 91-99.) https://doi.org/10.13064/KSSS.2014.6.4.091
  15. Yun, J. (2014). Analysis of Google Voice Actions' recognition ofEnglish word pronunciations by Korean young learners ofEnglish for the purpose of developing an English teachingassistant robot. M.A. Thesis, Kyungpook National University.(윤정희 (2014). Google 음성인식프로그램에 의한 한국 어린이 영어학습자의 영어단어 발음인식 실태분석: 영어학습도우미 로봇개발을 목적으로. 경북대학교 석사학위논문.)