# Prabhupadavani: A Code-mixed Speech Translation Data for 25 Languages

arXiv: https://arxiv.org/abs/2201.11391 · HTML: https://mlsanity.com/paper/2201.11391/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 28 references that are in the map.
- First posted on arXiv 27 Jan 2022.

## Builds on (most cited first, 13 of 13)

- [Sequence-to-Sequence Models Can Directly Translate Foreign Speech](https://mlsanity.com/paper/1703.08581/) (2017)
- [Direct speech-to-speech translation with a sequence-to-sequence model](https://mlsanity.com/paper/1904.06037/) (2019)
- [Europarl-ST: A Multilingual Corpus For Speech Translation Of Parliamentary Debates](https://mlsanity.com/paper/1911.03167/) (2019)
- [The Multilingual TEDx Corpus for Speech Recognition and Translation](https://mlsanity.com/paper/2102.01757/) (2021)
- [Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Text](https://mlsanity.com/paper/2006.00206/) (2020)
- [End-to-End Automatic Speech Translation of Audiobooks](https://mlsanity.com/paper/1802.04200/) (2018)
- [CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus](https://mlsanity.com/paper/2002.01320/) (2020)
- [A New Dataset for Natural Language Inference from Code-mixed Conversations](https://mlsanity.com/paper/2004.05051/) (2020)
- [MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible](https://mlsanity.com/paper/1907.12895/) (2019)
- [BSTC: A Large-Scale Chinese-English Speech Translation Dataset](https://mlsanity.com/paper/2104.03575/) (2021)
- [Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training](https://mlsanity.com/paper/1810.11895/) (2018)
- [Towards speech-to-text translation without speech recognition](https://mlsanity.com/paper/1702.03856/) (2017)
- [Challenges and Considerations with Code-Mixed NLP for Multilingual Societies](https://mlsanity.com/paper/2106.07823/) (2021)

## Built on by (most cited first, 2 of 2)

- [Generating Synthetic Speech from SpokenVocab for Speech Translation](https://mlsanity.com/paper/2210.08174/) (2022)
- [SanskritShala: A Neural Sanskrit NLP Toolkit with Web-Based Interface for Pedagogical and Annotation Purposes](https://mlsanity.com/paper/2302.09527/) (2023)

## Abstract (arXiv)

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.