@inproceedings{e-ojo-etal-2022-language,
    title = "Language Identification at the Word Level in Code-Mixed Texts Using Character Sequence and Word Embedding",
    author = "E. Ojo, O.  and
      Gelbukh, A.  and
      Calvo, H.  and
      Feldman, A.  and
      O. Adebanji, O.  and
      Armenta-Segura, J.",
    editor = "Chakravarthi, Bharathi Raja  and
      Murugappan, Abirami  and
      Chinnappa, Dhivya  and
      Hane, Adeep  and
      Kumeresan, Prasanna Kumar  and
      Ponnusamy, Rahul",
    booktitle = "Proceedings of the 19th International Conference on Natural Language Processing (ICON): Shared Task on Word Level Language Identification in Code-mixed Kannada-English Texts",
    month = dec,
    year = "2022",
    address = "IIIT Delhi, New Delhi, India",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.icon-wlli.1",
    pages = "1--6",
    abstract = "People often switch languages in conversations or written communication in order to communicate thoughts on social media platforms. The languages in texts of this type, also known as code-mixed texts, can be mixed at the sentence, word, or even sub-word level. In this paper, we address the problem of identifying language at the word level in code-mixed texts using a sequence of characters and word embedding. We feed machine learning and deep neural networks with a range of character-based and word-based text features as input. The data for this experiment was created by combining YouTube video comments from code-mixed Kannada and English (Kn-En) texts. The texts were pre-processed, split into words, and categorized as {`}Kannada{'}, {`}English{'}, {`}Mixed-Language{'}, {`}Name{'}, {`}Location{'}, and {`}Other{'}. The proposed techniques were able to learn from these features and were able to effectively identify the language of the words in the dataset. The proposed CK-Keras model with pre-trained Word2Vec embedding was our best-performing system, as it outperformed other methods when evaluated by the F1 scores.",
}