PhD thesis - School of Informatics - University of Edinburgh

More documents

Recommendations

Info

Chapter 6. Other Potential Applications 163 lingual vocalic databases, phone mapping algorithms and the building of an average voice by means of HMMs. The underlying goal of the first method is to achieve near perfect pronunciation of the foreign language inclusions. Although speakers are un- likely to pronounce foreign words perfectly, such a system would be very useful for multilingual TTS synthesis, for example to synthesise various paragraphs in different languages with the same voice as could be expected by an E-mail client of an interna- tional organisation. Another application area of this method could be foreign language teaching. However, the approach of building a multilingual voice database by means of a polyglot speaker is language-dependent and therefore difficult to extend to new languages. In comparison, the second method, phone mapping, is less dependent on the availability of speech resources and polyglot voice talents and therefore easier to expand to new language scenarios. Moreover, it is based on the assumption of ap- proximating speech sounds which is a prevalent phenomenon in the pronunciation of foreign words. Finally, the development of an average voice is the most language inde- pendent approach out of all three and therefore most easy to extend. However, the fact that is not as high quality as unit selection synthesis could have serious effects on the perception of a synthesised utterance in general and make differences in the synthesis of foreign inclusions less obvious to the listeners. Unfortunately, these methods have not been evaluated on real mixed-lingual utterances. Considering the results of production and perception studies of polyglot speech reviewed in Section 6.1.1.1, the phone mapping method appears as the most promising one with results that are likely to be most accepted in a subjective perception study. A readily available system set up for mixed-lingual synthesis would be ideal for a task-based TTS evaluation of the English inclusion classifier. Researchers at Nuance and Loquendo S.p.A. approach polyglot synthesis via multilingual vocalic databases and phone mapping, respectively. Either system would be interesting to test in a perception experiment. If such a system is not available, a voice needs to be created and the phoneme mapping algorithm imple- mented in order to be able to synthesise foreign inclusions. This can be facilitated by the speech synthesis system Festival 5 (Black and Taylor, 1997) and the FestVox 6 voice building tools. 5 http://www.cstr.ed.ac.uk/projects 6 http://www.festvox.org
Chapter 6. Other Potential Applications 164 6.1.5.1 Polyglot TTS system The main aim is to carry out synthesis experiments on German utterances containing English inclusions as a task-based evaluation of the English inclusion classifier in- troduced in this thesis. As previously mentioned, one version of the Loquendo TTS system is specifically designed for mixed-lingual input. The system is able to alternate between languages via the control tag \lang= in the markup of the input as shown in the example below. \lang= is used to return to the native language of the voice. 7 \lang=English Security-Tool \lang= verhindert, dass \lang=English Hacker \lang= über \lang=English Google \lang= Sicherheitslücken finden Translation: Security Tool prevents hackers from finding security holes via Google. Such a setup would allow for a perception experiment comparing an all German baseline synthesiser with one that is able to deal with foreign language inclusions. Three types of synthetic stimuli can be produced when using mixed-lingual input: (1) stimuli without markup for synthesis with the German baseline system, (2) stimuli marked up correctly for English inclusions for synthesis with a polyglot TTS system and (3) stimuli marked up by the English inclusion classifier for synthesis with a polyglot TTS system. The second type of stimuli will provide a clearer idea of whether the chosen polyglot TTS synthesis paradigm improves the output quality of mixed- lingual data. With this in mind, the third type of stimuli can then be used for the actual task-based evaluation of the foreign inclusion classifier. 6.1.5.2 Experimental Setup and Evaluation Before proposing exact details of the evaluation procedure, it should be reiterated that all factors learnt from previously described production and perception studies of mixed-lingual speech are likely to affect the results of the perception study of mixed- lingual TTS synthesis (see Section 6.1.1.1). Regarding subject-specific characteristics, age, level of English language skills and educational background must be controlled 7 A demo of this system is available online at: http://actor.loquendo.com/actordemo/ml. asp?language=en
Page 1 and 2:
Automatic Detection of English Incl
Page 3 and 4:
these parsers with the annotation-f
Page 5 and 6:
Declaration I declare that this the
Page 7 and 8:
3.3.5 Post-processing Module . . .
Page 9 and 10:
A.2.2 Kappa Coefficient . . . . . .
Page 11 and 12:
5.6 Average relative token frequenc
Page 13 and 14:
3.16 Most frequent English inclusio
Page 15 and 16:
Chapter 1. Introduction 2 siderable
Page 17 and 18:
Chapter 1. Introduction 4 Chapter 3
Page 19 and 20:
Chapter 1. Introduction 6 1.1 Relat
Page 21 and 22:
Chapter 2. Background and Theory 8
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
Page 37 and 38:
Page 39 and 40:
Page 41 and 42:
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
Chapter 3 Tracking English Inclusio
Page 61 and 62:
Chapter 3. Tracking English Inclusi
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Chapter 4 System Extension to a New
Page 115 and 116:
Chapter 4. System Extension to a Ne
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126: Chapter 4. System Extension to a Ne
Page 127 and 128: Chapter 4. System Extension to a Ne
Page 129 and 130: Chapter 5 Parsing English Inclusion
Page 131 and 132: Chapter 5. Parsing English Inclusio
Page 159 and 160: Chapter 6 Other Potential Applicati
Page 161 and 162: Chapter 6. Other Potential Applicat
Page 175: Chapter 6. Other Potential Applicat
Page 187 and 188: Chapter 7 Conclusions and Future Wo
Page 189 and 190: Chapter 7. Conclusions and Future W
Page 191 and 192: Appendix A. Evaluation Metrics and
Page 199 and 200: Appendix B. Guidelines for Annotati
Page 205 and 206: Appendix C TIGER Tags and Labels C.
Page 207 and 208: Appendix C. TIGER Tags and Labels 1
Page 209 and 210: Appendix C. TIGER Tags and Labels 1
Page 211 and 212: Bibliography 198 Andersen, G. (2005
Page 213 and 214: Bibliography 200 Bresnan, J. (2001)
Page 215 and 216: Bibliography 202 Damashek, M. (1995
Page 217 and 218: Bibliography 204 Finkel, J., Dingar
Page 219 and 220: Bibliography 206 Hachey, B., Alex,
Page 221 and 222: Bibliography 208 Kirkness, A. (1984
Page 223 and 224: Bibliography 210 and Technology (In
Page 225 and 226: Bibliography 212 Poplack, S. (1988)
Page 227 and 228:
Bibliography 214 Sokol, D. K. (2000
Page 229:
Bibliography 216 Yang, W. (1990). A
show all

PhD thesis - School of Informatics - University of Edinburgh

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?