@inproceedings{celano-2021-resnet,
title = "A {R}es{N}et-50-Based Convolutional Neural Network Model for Language {ID} Identification from Speech Recordings",
author = "Celano, Giuseppe G. A.",
editor = {Vylomova, Ekaterina and
Salesky, Elizabeth and
Mielke, Sabrina and
Lapesa, Gabriella and
Kumar, Ritesh and
Hammarstr{\"o}m, Harald and
Vuli{\'c}, Ivan and
Korhonen, Anna and
Reichart, Roi and
Ponti, Edoardo Maria and
Cotterell, Ryan},
booktitle = "Proceedings of the Third Workshop on Computational Typology and Multilingual NLP",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.sigtyp-1.13",
doi = "10.18653/v1/2021.sigtyp-1.13",
pages = "136--144",
abstract = "This paper describes the model built for the SIGTYP 2021 Shared Task aimed at identifying 18 typologically different languages from speech recordings. Mel-frequency cepstral coefficients derived from audio files are transformed into spectrograms, which are then fed into a ResNet-50-based CNN architecture. The final model achieved validation and test accuracies of 0.73 and 0.53, respectively.",
}
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%0 Conference Proceedings
%T A ResNet-50-Based Convolutional Neural Network Model for Language ID Identification from Speech Recordings
%A Celano, Giuseppe G. A.
%Y Vylomova, Ekaterina
%Y Salesky, Elizabeth
%Y Mielke, Sabrina
%Y Lapesa, Gabriella
%Y Kumar, Ritesh
%Y Hammarström, Harald
%Y Vulić, Ivan
%Y Korhonen, Anna
%Y Reichart, Roi
%Y Ponti, Edoardo Maria
%Y Cotterell, Ryan
%S Proceedings of the Third Workshop on Computational Typology and Multilingual NLP
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F celano-2021-resnet
%X This paper describes the model built for the SIGTYP 2021 Shared Task aimed at identifying 18 typologically different languages from speech recordings. Mel-frequency cepstral coefficients derived from audio files are transformed into spectrograms, which are then fed into a ResNet-50-based CNN architecture. The final model achieved validation and test accuracies of 0.73 and 0.53, respectively.
%R 10.18653/v1/2021.sigtyp-1.13
%U https://aclanthology.org/2021.sigtyp-1.13
%U https://doi.org/10.18653/v1/2021.sigtyp-1.13
%P 136-144
Markdown (Informal)
[A ResNet-50-Based Convolutional Neural Network Model for Language ID Identification from Speech Recordings](https://aclanthology.org/2021.sigtyp-1.13) (Celano, SIGTYP 2021)
ACL