@inproceedings{celano-2022-transformer,
    title = "A Transformer Architecture for the Prediction of Cognate Reflexes",
    author = "Celano, Giuseppe G. A.",
    editor = "Vylomova, Ekaterina  and
      Ponti, Edoardo  and
      Cotterell, Ryan",
    booktitle = "Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP",
    month = jul,
    year = "2022",
    address = "Seattle, Washington",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.sigtyp-1.10/",
    doi = "10.18653/v1/2022.sigtyp-1.10",
    pages = "80--85",
    abstract = "This paper presents the transformer model built to participate in the SIGTYP 2022 Shared Task on the Prediction of Cognate Reflexes. It consists of an encoder-decoder architecture with multi-head attention mechanism. Its output is concatenated with the one hot encoding of the language label of an input character sequence to predict a target character sequence. The results show that the transformer outperforms the baseline rule-based system only partially."
}