Applications of Multilingual Phone Recognition in Code-Switched and Non-code-Switched Scenarios-Reference-Cited by-同舟云学术

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Applications of Multilingual Phone Recognition in Code-Switched and Non-code-Switched Scenarios

Published:2021-07-07 Issue: Volume: Page:67-83
ISSN:2191-737X
Container-title:SpringerBriefs in Speech Technology
language:
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Author:

Manjunath K. E.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-80741-2_6

Reference29 articles.

1. C. Chang, C. Lin, LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3), 1–27 (2011). https://doi.org/10.1145/1961189.1961199

2. K.E. Manjunath, S.S. Kumar, D. Pati, B. Satapathy, K.S. Rao, Development of consonant-vowel recognition systems for Indian languages: Bengali and Odia, in IEEE India Conference on Emerging Trends and Innovation in Technology (INDICON) (2013), pp. 1–6. https://doi.org/10.1109/INDCON.2013.6726109

3. scikit-learn, Scikit-learn: machine learning in Python—Online documentation. https://scikit-learn.org [Accessed Mar. 08, 2020]

4. N. Dehak, P.A. Torres-Carrasquillo, D. Reynolds, R. Dehak, Language recognition via i-vectors and dimensionality reduction, in INTERSPEECH (2011), pp. 857–860

5. D.A. Reynolds, T.F. Quatieri, R.B. Dunn, Speaker verification using adapted Gaussian mixture models, in Digital Signal Processing (2000), pp. 19–41

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1. An Overview of Indian Spoken Language Recognition from Machine Learning Perspective;ACM Transactions on Asian and Low-Resource Language Information Processing;2022-11-12

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