William Byrne
Affiliations: | University of Cambridge, Cambridge, England, United Kingdom |
Area:
Speech processingWebsite:
http://mi.eng.cam.ac.uk/~wjb31/Google:
"William Byrne"Cross-listing: Neurotree
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Publications
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| Shannon M, Zen H, Byrne W. (2013) Autoregressive models for statistical parametric speech synthesis Ieee Transactions On Audio, Speech and Language Processing. 21: 587-597 |
| Dines J, Liang H, Saheer L, et al. (2013) Personalising speech-to-speech translation: Unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis Computer Speech and Language. 27: 420-437 |
| De Gispert A, Blackwood G, Iglesias G, et al. (2013) N-gram posterior probability confidence measures for statistical machine translation: An empirical study Machine Translation. 27: 85-114 |
| Pino J, Waite A, Byrne W. (2012) Simple and Efficient Model Filtering in Statistical Machine Translation The Prague Bulletin of Mathematical Linguistics. 98: 5-24 |
| Hashimoto K, Yamagishi J, Byrne W, et al. (2012) Impacts of machine translation and speech synthesis on speech-to-speech translation Speech Communication. 54: 857-866 |
| Gibson M, Byrne W. (2011) Unsupervised intralingual and cross-lingual speaker adaptation for HMM-Based speech synthesis using two-pass decision tree construction Ieee Transactions On Audio, Speech and Language Processing. 19: 895-904 |
| de Gispert A, Iglesias G, Blackwood G, et al. (2010) Hierarchical Phrase-Based Translation with Weighted Finite-State Transducers and Shallow-n Grammars Computational Linguistics. 36: 505-533 |
| Deng Y, Byrne W. (2008) HMM word and phrase alignment for statistical machine translation Ieee Transactions On Audio, Speech and Language Processing. 16: 494-507 |
| Venkataramani V, Chakrabartty S, Byrne W. (2007) Ginisupport vector machines for segmental minimum Bayes risk decoding of continuous speech Computer Speech and Language. 21: 423-442 |
| Goel V, Kumar S, Byrne W. (2006) Corrections to "Segmental minimum Bayes-risk decoding for automatic speech recognition" Ieee Transactions On Audio, Speech and Language Processing. 14: 356-357 |