Generating non-native pronunciation variants for lexicon adaptation

Speech Communication

Volumn 42, Issue 1, 2004, Pages 109-123

  Goronzy, Silke ^a   Rapp, Stefan ^a   Kompe, Ralf ^a  

^a Sony Deutschland GmbH   (Germany)

Author keywords

Non native speech; Pronunciation modelling; Speaker adaptation

Indexed keywords

ACOUSTIC NOISE; DATABASE SYSTEMS; GLOSSARIES; LINGUISTICS; MARKOV PROCESSES; PERFORMANCE; PUBLIC ADDRESS SYSTEMS; SPEECH COMMUNICATION;

PRONUNCIATION MODELING; SPEAKER ADAPTATION;

SPEECH RECOGNITION;

EID: 0346008163     PISSN: 01676393     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.specom.2003.09.003     Document Type: Conference Paper

References (34)

1. Adda-Decker M., Lamel L. Pronunciation variation across system configuration, language and speaking style. Speech Comm. 29:1999;88-98.
2. Amdal, I., Korkmazskiy, F., Suredan, A.C., 2000. Data-driven pronunciation modelling for non-native speakers using association strength between phones. In: ASRU2000, Vol. 1, Paris, pp. 85-90.
3. Batliner, A., Möbius, B., Schweitzer, A., Goronzy, S., Rapp, S., Regel-Brietzmann, P., 2001. SMARTKOM Technical Report 16, Guidelines for 'Text-to-Phone' (TTP) conversion for the SMARTKOM lexicon. Available from 〈http://www.smartkom.org 〉.
4. Cremelie, N., Martens, J.-P., 1997. Automatic rule-based generation of word pronunciation networks. In: Eurospeech97, Rhodes, pp. 2459-2462.
5. C5.0. Available from 〈http://www.rulequest.com〉.
6. di Mori R. Spoken Dialogues with Computers. 1998;Academic Press.
7. Downey, S., Wiseman, R., 1998. Dynamic and static improvements to lexical baseforms. In: Workshop on Modeling Pronunciation Variation, Rolduc, pp. 157-162.
8. Eisele, K.N.M., 2002. Deriving non-native pronunciation variants without using non-native data. In: Diploma thesis, Department of Computer Science, Karlsruhe University of Applied Sciences.
9. Flege J.E. The production of "New" and "Similar" phones in a foreign language: evidence for the effect of equivalence classification. J. Phonet. 15(1):1987;47-65.
10. Fosler-Lussier, E., 1999. Multi-level decision trees for static and dynamic pronunciation models. In: Eurospeech99, Budapest, pp. 463-466.
11. Goronzy, S., 2002. Robust Adaptation to Non-Native Accents in Automatic Speech Recognition. Springer Verlag, Lecture Notes on Artificial Intelligence 2560.
12. Goronzy, S., Kompe, R., 1999. A MAP-like weighting scheme for MLLR speaker adaptation. In: Eurospeech99, Budapest, pp. 5-8.
13. Goronzy, S., Sahakyan, M., Wokurek, W., 2001. Is non-native pronunciation. Modelling necessary? In: Eurospeech2001, Vol. 1, pp. 309-312.
14. He, X., Zhao, Y., 2001. Model complexity optimization for nonnative english speakers. In: Eurospeech2001, Vol. 2, pp. 1461-1464.
15. Holter T., Svendsen T. Maximum likelihood modelling of pronunciation variation. Speech Comm. 29:1999;177-191.
16. Huang, C., Chang, E., Zhou, J., Lee, K.-F., 2000. Accent modeling based on pronunciation dictionary adaptation for large vocabulary mandarin speech recognition. In: ICSLP2000, Vol. 3, pp. 818-821.
17. Humphries, J.J., Woodland, P.C., Pearce, D., 1996. Using accent-specific pronunciation modelling for robust speech recognition. In: ICSLP96, Vol. 4, pp. 2324-2327.
18. ISLE. Interactive Spoken Language Education. Available from 〈http://nats-www.informatik.uni-hamburg.de/̃isle/〉.
19. Jurafsky, D., Ward, W., Jianping, Z., Herold, K., Xiuyang, Y., Sen, Z., 2001. What kind of pronunciation variation is hard for triphones to model? In: ICASSP2001, Salt Lake City, Vol. 1, pp. 577-580.
20. Kat, L.W., Fung, P., 2000. MLLR-based accent model adaptation without accented data. In: ICSLP2000, Beijing, Vol. 3, pp. 738-741.
21. Kipp, A., Wesenick, M.-A., Schiel, F., 1996. Automatic detection and segmentation of pronunciation variants in german speech corpora. In: ICSLP96, Philadelphia, Vol. 1, pp. 106-109.
22. Kipp, A., Wesenick, M.-A., Schiel, F., 1997. Pronunciation modeling applied to automatic segmentation of spontaneous speech. In: Eurospeech97, Rhodes, Vol. 2, pp. 1023-1026.
23. Riley M., Byrne W., Finke M., Khudanpur S., Ljolie A., McDonough J., Nock H., Saraclar M., Wooters C., Zavaliagkos G. Stochastic pronunciation modelling from hand-labelled phonetic corpora. Speech Comm. 29:1999;209-224.
24. SAMPA. Available from 〈http://www.phon.ucl.ac.uk/home/sampa/home.htm〉.
25. Sahakyan, M., 2001. Variantenlexikon italienischer und deutscher Lerner des Englischen für die automatische Spracherkennung. Diploma thesis, IMS, University of Stuttgart.
26. Sloboda, T., Waibel, A., 1996. Dictionary learning for spontaneous speech recognition. In: ICSLP96, Vol. 4, pp. 2328-2331.
27. Strik, H., 2001. Pronunciation at the lexical level. In: ISCA ITR-Workshop on Adaptation Methods for Speech Recognition, Sophia-Antiolis, France, Vol. 1, pp. 123-130.
28. Strik H., Cucchiarini C. Modeling pronunciation variation for ASR: A survey of the literature. Speech Comm. 29:1999;225-246.
29. Wester, M., Fosler-Lussier, E., 2000. A comparison of data-derived knowledge-based modeling of pronunciation variation. In: ICSLP2000, Vol. 1, pp. 270-273.
30. Wester, M., Kessens, J.M., Strik, H., 1998. Improving the performance of a Dutch CSR by modeling pronunciation variation. In: ESCA Workshop on Modeling Pronunciation Variation, Vol. 1, pp. 145-150.
31. Williams, G., Renals, S., 1998. Confidence measures for evaluating pronunciation models. In: Workshop on Modeling Pronunciation Variation, Rolduc, Vol. 1, pp. 151-155.
32. Witt, S., Young, S., 1999. Off-line acoustic modeling of non-native accents. In: Eurospeech99, Budapest, pp. 1367-1370.
33. Woodland, P.C., 1999. Speaker Adaptation: Techniques and Challenges. In: ASRU99, Vol. 1, pp. 85-90.
34. Yang, Q., Martens, J.-P., 2000. On the importance of exception and cross-word rules for the data-driven creation of Lexica for ASR. ProRISC2000 Workshop on Circuits, Systems and Signal Processing.