| Autor: |
Kumar, Sujit, Rajesh, Devesh D., Pranesh, Sarthak, Kollipara, V. N. Hemanth, Agrawal, Gopal Kumar, Anbarasi, M., Valarmathi J. |
| Předmět: |
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| Zdroj: |
International Journal of Cognitive Computing in Engineering; Jun2022, Vol. 3, p114-123, 10p |
| Abstrakt: |
Automatic speech recognition is being used everywhere these days. An essential part of this is language identifi- cation. Our goal here is to identify the language of the media title, such as song names and movie titles, to help in speech recognition. The focus here is to classify solely using the title of the media without any additional data in their transliterated form to classify them into their original native language using natural language processing, machine learning, and deep learning techniques. Transliterated titles of the song and movie names are being used. This work explores and implements various natural language processing and machine learning methods such as N-grams, SVMs, LSTMs, and MuRIL to classify the text titles according to their language. The results of various implementations are compared and contrasted as an approach of its own to classify the data. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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