@inproceedings{alastruey-etal-2023-towards,
title = "Towards Real-World Streaming Speech Translation for Code-Switched Speech",
author = "Alastruey, Belen and
Sperber, Matthias and
Gollan, Christian and
Telaar, Dominic and
Ng, Tim and
Agarwal, Aashish",
editor = "Winata, Genta and
Kar, Sudipta and
Zhukova, Marina and
Solorio, Thamar and
Diab, Mona and
Sitaram, Sunayana and
Choudhury, Monojit and
Bali, Kalika",
booktitle = "Proceedings of the 6th Workshop on Computational Approaches to Linguistic Code-Switching",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.calcs-1.2",
doi = "10.18653/v1/2023.calcs-1.2",
pages = "14--22",
abstract = "Code-switching (CS), i.e. mixing different languages in a single sentence, is a common phenomenon in communication and can be challenging in many Natural Language Processing (NLP) settings. Previous studies on CS speech have shown promising results for end-to-end speech translation (ST), but have been limited to offline scenarios and to translation to one of the languages present in the source monolingual transcription). In this paper, we focus on two essential yet unexplored areas for real-world CS speech translation: streaming settings, and translation to a third language (i.e., a language not included in the source). To this end, we extend the Fisher and Miami test and validation datasets to include new targets in Spanish and German. Using this data, we train a model for both offline and streaming ST and we establish baseline results for the two settings mentioned earlier.",
}
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<abstract>Code-switching (CS), i.e. mixing different languages in a single sentence, is a common phenomenon in communication and can be challenging in many Natural Language Processing (NLP) settings. Previous studies on CS speech have shown promising results for end-to-end speech translation (ST), but have been limited to offline scenarios and to translation to one of the languages present in the source monolingual transcription). In this paper, we focus on two essential yet unexplored areas for real-world CS speech translation: streaming settings, and translation to a third language (i.e., a language not included in the source). To this end, we extend the Fisher and Miami test and validation datasets to include new targets in Spanish and German. Using this data, we train a model for both offline and streaming ST and we establish baseline results for the two settings mentioned earlier.</abstract>
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%0 Conference Proceedings
%T Towards Real-World Streaming Speech Translation for Code-Switched Speech
%A Alastruey, Belen
%A Sperber, Matthias
%A Gollan, Christian
%A Telaar, Dominic
%A Ng, Tim
%A Agarwal, Aashish
%Y Winata, Genta
%Y Kar, Sudipta
%Y Zhukova, Marina
%Y Solorio, Thamar
%Y Diab, Mona
%Y Sitaram, Sunayana
%Y Choudhury, Monojit
%Y Bali, Kalika
%S Proceedings of the 6th Workshop on Computational Approaches to Linguistic Code-Switching
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F alastruey-etal-2023-towards
%X Code-switching (CS), i.e. mixing different languages in a single sentence, is a common phenomenon in communication and can be challenging in many Natural Language Processing (NLP) settings. Previous studies on CS speech have shown promising results for end-to-end speech translation (ST), but have been limited to offline scenarios and to translation to one of the languages present in the source monolingual transcription). In this paper, we focus on two essential yet unexplored areas for real-world CS speech translation: streaming settings, and translation to a third language (i.e., a language not included in the source). To this end, we extend the Fisher and Miami test and validation datasets to include new targets in Spanish and German. Using this data, we train a model for both offline and streaming ST and we establish baseline results for the two settings mentioned earlier.
%R 10.18653/v1/2023.calcs-1.2
%U https://aclanthology.org/2023.calcs-1.2
%U https://doi.org/10.18653/v1/2023.calcs-1.2
%P 14-22
Markdown (Informal)
[Towards Real-World Streaming Speech Translation for Code-Switched Speech](https://aclanthology.org/2023.calcs-1.2) (Alastruey et al., CALCS-WS 2023)
ACL