indspeech_newstra_ethnicsr

INDspeech_NEWSTRA_EthnicSR is a collection of graphemically balanced and parallel speech corpora of four major Indonesian ethnic languages: Javanese, Sundanese, Balinese, and Bataks. It was developed in 2013 by the Nara Institute of Science and Technology (NAIST, Japan) [Sakti et al., 2013]. The data has been used to develop Indonesian ethnic speech recognition in supervised learning [Sakti et al., 2014] and semi-supervised learning [Novitasari et al., 2020] based on Machine Speech Chain framework [Tjandra et al., 2020].

Dataset Usage

Run pip install nusacrowd before loading the dataset through HuggingFace's load_dataset.

Citation

@inproceedings{sakti-cocosda-2013,
    title = "Towards Language Preservation: Design and Collection of Graphemically Balanced and Parallel Speech Corpora of {I}ndonesian Ethnic Languages",
    author = "Sakti, Sakriani and Nakamura, Satoshi",
    booktitle = "Proc. Oriental COCOSDA",
    year = "2013",
    address = "Gurgaon, India"
}

@inproceedings{sakti-sltu-2014,
  title = "Recent progress in developing grapheme-based speech recognition for {I}ndonesian ethnic languages: {J}avanese, {S}undanese, {B}alinese and {B}ataks",
  author = "Sakti, Sakriani and Nakamura, Satoshi",
  booktitle = "Proc. 4th Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU 2014)",
  year = "2014",
  pages = "46--52",
  address = "St. Petersburg, Russia"
}

@inproceedings{novitasari-sltu-2020,
  title = "Cross-Lingual Machine Speech Chain for {J}avanese, {S}undanese, {B}alinese, and {B}ataks Speech Recognition and Synthesis",
  author = "Novitasari, Sashi and Tjandra, Andros and Sakti, Sakriani and Nakamura, Satoshi",
  booktitle = "Proc. Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)",
  year = "2020",
  pages = "131--138",
  address = "Marseille, France"
}

License

CC-BY-NC-SA 4.0

Homepage

https://github.com/s-sakti/data_indsp_newstra_ethnicsr

NusaCatalogue

For easy indexing and metadata: https://indonlp.github.io/nusa-catalogue