The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
The voice bank corpus: Design, collection and data analysis of a large regional accent speech database
Abstract
The University of Edinburgh has started the development of a new speech database, the Voice Bank corpus, specifically designed for the creation of personalised synthetic voices for individuals with speech disorders. This corpus already constitutes the largest corpora of British English currently in existence, with more than 300 hours of recordings from approximately 500 healthy speakers. New recordings are continuously being made in order to get the best coverage of the different combinations of regional accents, social classes, age and gender across Britain. This paper describes the motivation and the processes involved in the design and recording of this corpus as well as some analysis of its content. The paper concludes with our future plans to further extend this corpus and to overcome its current limitations.
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A robust parser for spoken language understanding
Wang, Y.-Y. (1999) · 6th European Conference on Speech Communication and Technology · doi:10.21437/eurospeech.1999-513 · Cited by 653
Sociolinguistic Patterns in British English
Durmuller, U., & Trudgill, P. (1980) · Language · doi:10.2307/412686 · Cited by 414
WSJCAMO: a British English speech corpus for large vocabulary continuous speech recognition
Robinson, T., Fransen, J., Pye, D., Foote, J., & Renals, S. (2002) · 1995 International Conference on Acoustics, Speech, and Signal Processing · doi:10.1109/icassp.1995.479278 · Cited by 353
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Self-citationGood‐turing frequency estimation without tears*
Gale, W. A., & Sampson, G. (1995) · Journal of Quantitative Linguistics · doi:10.1080/09296179508590051 · Cited by 314
Simultaneous Modeling Of Spectrum, Pitch And Duration In HMM-Based Speech Synthesis
Yoshimura, T., Tokuda, K., Kobayashi, T., Masuko, T., & Kitamura, T. (1999) · Cited by 166
Festival Speech Synthesis System
Black, A. W., Taylor, P., & Caley, R. (2000) · Americanae (AECID Library) · Cited by 137
Yamagishi, J., Usabaev, B., King, S., Watts, O., Dines, J., Tian, J., Guan, Y., Hu, R., Oura, K., Wu, Y.-J., et al. (2010) · IEEE Transactions on Audio, Speech, and Language Processing · doi:10.1109/tasl.2010.2045237 · Cited by 78 · cited 1×
“This technique, referred to as speaker adaptation, has already been successfully applied to “non traditional TTS” corpora such as ASR corpora, which contains a large number of speakers [4].”
MethodSelf-citationGood-Turing Smoothing Without Tears
Gale, W. A. (2001) · Cited by 76
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SpeechBrain: A General-Purpose Speech Toolkit
Ravanelli, M., Parcollet, T., Plantinga, P., Rouhe, A., Cornell, S., Lugosch, L., Subakan, C., Dawalatabad, N., Heba, A., Zhong, J., et al. (2021) · arXiv · doi:10.48550/arxiv.2106.04624 · Cited by 512
Real-Time Speech Enhancement Using Equilibriated RNN
Takeuchi, D., Yatabe, K., Koizumi, Y., Oikawa, Y., & Harada, N. (2020) · ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp40776.2020.9054597 · Cited by 48
(2017) · doi:10.7488/ds/1994 · Cited by 35
Metadata
- Authors
- Veaux, C., Yamagishi, J., & King, S.
- Venue
- 2013 International Conference Oriental COCOSDA held jointly with 2013 Conference on Asian Spoken Language Research and Evaluation (O-COCOSDA/CASLRE)
- Publisher
- IEEE
- Published
- 2013-11
- Pages
- 1-4
- OpenAlex
- W2094721231
- Cited by
- 398
- References
- 14
- FWCI
- 1.73
- Type
- conference paper
- Language
- en
- Open access
- closed
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