Prabhupadavani: A Code-mixed Speech Translation Data for 25 Languages
This provides a resource for researchers in speech translation and machine translation to address code-mixing, particularly in humanities teaching contexts, but it is incremental as it primarily offers new data rather than a novel method.
The authors tackled the lack of labeled data for code-mixed speech translation by introducing Prabhupadavani, a multilingual dataset for 25 languages containing 94 hours of speech manually aligned with text, focusing on Vedic culture and heritage.
Nowadays, the interest in code-mixing has become ubiquitous in Natural Language Processing (NLP); however, not much attention has been given to address this phenomenon for Speech Translation (ST) task. This can be solely attributed to the lack of code-mixed ST task labelled data. Thus, we introduce Prabhupadavani, which is a multilingual code-mixed ST dataset for 25 languages. It is multi-domain, covers ten language families, containing 94 hours of speech by 130+ speakers, manually aligned with corresponding text in the target language. The Prabhupadavani is about Vedic culture and heritage from Indic literature, where code-switching in the case of quotation from literature is important in the context of humanities teaching. To the best of our knowledge, Prabhupadvani is the first multi-lingual code-mixed ST dataset available in the ST literature. This data also can be used for a code-mixed machine translation task. All the dataset can be accessed at https://github.com/frozentoad9/CMST.