Development of accurate automated language identification model using polymer pattern and tent maximum absolute pooling techniques-Reference-Cited by-同舟云学术

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Development of accurate automated language identification model using polymer pattern and tent maximum absolute pooling techniques

Published:2022-01-20 Issue:6 Volume:34 Page:4875-4888
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Tuncer Turker,Dogan Sengul,Akbal Erhan,Cicekli Abdullah,Rajendra Acharya U.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-06678-0.pdf

Reference55 articles.

1. Rosenthal S, Atanasova P, Karadzhov G, Zampieri M, Nakov P (2020) A large-scale semi-supervised dataset for offensive language identification. arXiv preprint

2. Takçi H, Ekinci E (2012) Minimal feature set in language identification and finding suitable classification method with it. Procedia Technol 1:444–448

3. Habic V, Semenov A, Pasiliao EL (2020) Multitask deep learning for native language identification. Knowl Based Syst 209:106440

4. Guha S, Das A, Singh PK, Ahmadian A, Senu N, Sarkar R (2020) Hybrid feature selection method based on harmony search and naked mole-rat algorithms for spoken language identification from audio signals. IEEE Access 8:182868–182887

5. Mukherjee H, Obaidullah SM, Santosh K, Phadikar S, Roy K (2020) A lazy learning-based language identification from speech using MFCC-2 features. Int J Mach Learn Cybern 11(1):1–14

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