Читать книгу The Concise Encyclopedia of Applied Linguistics - Carol A. Chapelle - Страница 222

1 Anagnostopoulos, C.‐N., Iliou, T., & Glannoukos, I. (2015). Features and classifiers for emotion recognition from speech: A survey from 2000 to 2011. Artificial Intelligence Review, 43(2), 155–77.

2 Anderson, J. N., Davidson, N., Morton, H., & Jack, M. A. (2008). Language learning with interactive virtual agent scenarios and speech recognition: Lessons learned. Computer Animation and Virtual Worlds, 19, 605–19.

3 Bernstein, J., Najmi, A., & Ehsani, F. (1999). Subarashii: Encounters in Japanese spoken language education. CALICO Journal, 16(3), 361–84.

4 Burileanu, D. (2008). Spoken language interfaces for embedded applications. In D. Gardner‐Bonneau & H. E. Blanchard (Eds.), Human factors and voice interactive systems (2nd ed., pp. 135–61). Norwell, MA: Springer.

5 Cucchiarini, C., Neri, A., & Strik, H. (2009). Oral proficiency training in Dutch L2: The contribution of ASR‐based corrective feedback. Speech Communication, 51(10), 853–63.

6 Dalby, J., & Kewley‐Port, D. (1999). Explicit pronunciation training using automatic speech recognition technology. CALICO Journal, 16(3), 425–45.

7 Davis, K. H., Biddulph, R., & Balashek, S. (1952). Automatic recognition of spoken digits. The Journal of the Acoustical Society of America, 24(6), 637–42.

8 Deng, L., Li, J., Huang, J.‐T., Yao, K., Yu, D., Seide, F., . . . & Acero, A. (2013). Recent advances in deep learning for speech research at Microsoft. In Acoustics, Speech and Signal Processing (ICASSP), IEEE International Conference (pp. 8604–8). Piscataway, NJ: IEEE.

9 Deng, L., & Yu, D. (2014). Deep learning: Methods and applications. Foundations and Trends® in Signal Processing, 7(3–4), 197–387.

10 Derwing, T. M., Munro, M. J., & Carbonaro, M. (2000). Does popular speech recognition software work with ESL speech? TESOL Quarterly, 34, 592–603.

11 Duan, R., Kawahara, T., Dantsuji, M., & Zhang, J. (2017). Effective articulatory modeling for pronunciation error detection of L2 learner without non‐native training data. In Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference (pp. 5815–19). Piscataway, NJ: IEEE.

12 Eskenazi, M. (1999). Using a computer in foreign language pronunciation training: What advantages? CALICO Journal, 16(3), 447–69.

13 Forgie, J. W., & Forgie, C. D. (1959). Results obtained from a vowel recognition computer program. The Journal of the Acoustical Society of America, 31(11), 1480–9.

14 Harless, W., Zier, M., & Duncan, R. (1999). Virtual dialogues with native speakers: The evaluation of an interactive multimedia method. CALICO Journal, 16(3), 313–37.

15 Lai, J., Karat, C.‐M., & Yankelovich, N. (2008). Conversational speech interfaces and technologies. In A. Sears & J. A. Jacko (Eds.), The human‐computer interaction handbook: Fundamentals, evolving technologies, and emerging applications (2nd ed., pp. 381–91). New York, NY: Erlbaum.

16 Liakin, D., Cardoso, W., & Liakina, N. (2017). The pedagogical use of mobile speech synthesis (TTS): Focus on French liaison. Computer Assisted Language Learning, 30(3–4), 348–65.

17 Liew, A., & Wang, S. (2009). Visual speech recognition: Lip segmentation and mapping. Hershey, PA: Medical Information Science Reference.

18 Markowitz, J. A. (1996). Using speech recognition. Upper Saddle River, NJ: Prentice Hall.

19 Martin, T. B., Nelson, A. L., & Zadell, H. J. (1964). Speech recognition by feature abstraction techniques (Technical Report AL‐TDR‐64‐176). Wright‐Patterson Airforce Base, OH: Air Force Avionics Lab.

20 McCrocklin, S. M. (2016). Pronunciation learner autonomy: The potential of automatic speech recognition. System, 57, 25–42.

21 Mitra, V., Franco, H., Stern, R., Van Hout, J., Ferrer, L., Graciarena, M., . . . & Hansen, J. H. L. (2017). Robust features in deep learning‐based speech recognition. In S. Watanabe, M. Delcroix, F. Metze, & J. R. Hershey (Eds.), New era of robust speech recognition: Exploiting deep learning (pp. 187–217). Cham, Switzerland: Springer.

22 Mohamed, A., Dahl, G. E., & Hinton, G. (2012). Acoustic modeling using deep belief networks. IEEE Transactions on Audio, Speech, and Language Processing, 20(1), 14–22.

23 Mostow, J., & Aist, G. (1999). Giving help and praise in a reading tutor with imperfect listening—because automated speech recognition means never being able to say you're certain. CALICO Journal, 16(3), 407–24.

24 Neri, A., Cucchiarini, C., Strik, H., & Boves, L. (2002). The pedagogy‐technology interface in computer assisted pronunciation training. Computer‐Assisted Language Learning, 15(5), 441–67.

25 Neumeyer, L., Franco, H., Digalakis, V., & Weintraub, M. (2000). Automatic scoring of pronunciation quality. Speech Communication, 30, 83–93.

26 O'Brien, M. (2006). Teaching pronunciation and intonation with computer technology. In L. Ducate & N. Arnold (Eds.), Calling on CALL: From theory and research to new directions in foreign language teaching (pp. 127–48). San Marcos, Texas: Calico Monograph Series.

27 Pan, J., Liu, C., Wang, Z., Hu, Y., & Jiang, H. (2012). Investigation of deep neural networks (DNN) for large vocabulary continuous speech recognition: Why DNN surpasses GMMs in acoustic modeling. In The 8th International Symposium on Chinese Spoken Language Processing (ISCSLP), 301–5.

28 Peinado, A. M., & Segura, J. C. (2006). Speech recognition over digital channels: Robustness and standards. Chichester, England: John Wiley.

29 Poulsen, R., Hastings, P., & Allbritton, D. (2007). Tutoring bilingual students with an automated reading tutor that listens. Journal of Educational Computing Research, 36(2), 191–221.

30 Rabiner, L., & Juang, B.‐H. (1993). Fundamentals of speech recognition. Englewood Cliffs, NJ: Prentice Hall.

31 Reddy, D. (1966). An approach to computer speech recognition by direct analysis of the speech wave (Technical Report No. C549). Stanford, CA: Stanford University.

32 Rodman, R. D. (1999). Computer speech technology. Norwood, MA: Artech House.

33 Schuller, B., Batliner, A., Steidl, S., & Seppi, D. (2009). Emotion recognition from speech: Putting ASR in the loop. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ‘09) (pp. 4585–8). Taipei, Taiwan: IEEE.

34 Torkkola, K. (1994). Stochastic models and artificial neural networks for automatic speech recognition. In E. Keller (Ed.), Fundamentals of speech synthesis and speech recognition (pp. 149–69). Chichester, England: John Wiley.

35 Truong, K., Neri, A., de Wet, F., Cucchiarini, C., & Strik, H. (2005). Automatic detection of frequent pronunciation errors made by L2 learners. Proceedings of InterSpeech (pp. 1345–8). Lisbon, Portugal.

36 Vintsyuk, T. K. (1968). Speech discrimination by dynamic programming. Kibernetika, 4(2), 81–8.

37 Witt, S., & Young, S. (2000). Phone‐level pronunciation scoring and assessment for interactive language learning. Speech Communication, 30, 95–108.

38 Yu, D., & Deng, L. (2015). Automatic speech recognition: A deep learning approach. London, England: Springer.

39 Zhang, Z., Geiger, J., Pohjalainen, J., Mousa, A. E., Jin, W., & Schuller, B. (2017). Deep learning for environmentally robust speech recognition: An overview of recent developments. Retrieved April 3, 2019 from https://arxiv.org/abs/1705.10874