The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.
Spoken Language Recognition: From Fundamentals to Practice
Abstract
Spoken language recognition refers to the automatic process through which we determine or verify the identity of the language spoken in a speech sample. We study a computational framework that allows such a decision to be made in a quantitative manner. In recent decades, we have made tremendous progress in spoken language recognition, which benefited from technological breakthroughs in related areas, such as signal processing, pattern recognition, cognitive science, and machine learning. In this paper, we attempt to provide an introductory tutorial on the fundamentals of the theory and the state-of-the-art solutions, from both phonological and computational aspects. We also give a comprehensive review of current trends and future research directions using the language recognition evaluation (LRE) formulated by the National Institute of Standards and Technology (NIST) as the case studies.
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Cited by
Speech Recognition Using Deep Neural Networks: A Systematic Review
Nassif, A. B., Shahin, I., Attili, I., Azzeh, M., & Shaalan, K. (2019) · IEEE Access · doi:10.1109/access.2019.2896880 · Cited by 1,152
Spoofing and countermeasures for speaker verification: A survey
Wu, Z., Evans, N., Kinnunen, T., Yamagishi, J., Alegre, F., & Li, H. (2015) · Speech Communication · doi:10.1016/j.specom.2014.10.005 · Cited by 601
Self-citationVoice conversion versus speaker verification: an overview
Wu, Z., & Li, H. (2014) · APSIPA Transactions on Signal and Information Processing · doi:10.1017/atsip.2014.17 · Cited by 45
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Metadata
- Authors
- Li, H., Ma, B., & Lee, K. A.
- Venue
- Proceedings of the IEEE
- Published
- 2013-05
- Volume
- 101
- Issue
- 5
- Pages
- 1136-1159
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2104457544
- Cited by
- 296
- References
- 67
- FWCI
- 29.82
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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