---
dataset_info:
  features:
  - name: language
    dtype: string
  - name: text
    sequence: string
  - name: label
    sequence: string
  splits:
  - name: train
    num_bytes: 8854308
    num_examples: 24453
  - name: test
    num_bytes: 1053019
    num_examples: 2711
  download_size: 1806180
  dataset_size: 9907327
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
language:
- hi
- te
- ta
- mr
- bn
- kn
---
# Cite

```
@inproceedings{kochar-etal-2024-towards,
    title = "Towards Disfluency Annotated Corpora for {I}ndian Languages",
    author = "Kochar, Chayan  and
      Mujadia, Vandan Vasantlal  and
      Mishra, Pruthwik  and
      Sharma, Dipti Misra",
    editor = "Jha, Girish Nath  and
      L., Sobha  and
      Bali, Kalika  and
      Ojha, Atul Kr.",
    booktitle = "Proceedings of the 7th Workshop on Indian Language Data: Resources and Evaluation",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.wildre-1.1/",
    pages = "1--10",
    abstract = "In the natural course of spoken language, individuals often engage in thinking and self-correction during speech production. These instances of interruption or correction are commonly referred to as disfluencies. When preparing data for subsequent downstream NLP tasks, these linguistic elements can be systematically removed, or handled as required, to enhance data quality. In this study, we present a comprehensive research on disfluencies in Indian languages. Our approach involves not only annotating real-world conversation transcripts but also conducting a detailed analysis of linguistic nuances inherent to Indian languages that are necessary to consider during annotation. Additionally, we introduce a robust algorithm for the synthetic generation of disfluent data. This algorithm aims to facilitate more effective model training for the identification of disfluencies in real-world conversations, thereby contributing to the advancement of disfluency research in Indian languages."
}
```