README.md

metadata

license: cc-by-4.0
dataset_info:
  - config_name: assamese
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  - config_name: bengali
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  - config_name: bodo
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  - config_name: dogri
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  - config_name: gujarati
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  - config_name: hindi
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  - config_name: kannada
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  - config_name: kashmiri
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  - config_name: konkani
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  - config_name: maithili
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  - config_name: malayalam
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  - config_name: manipuri
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  - config_name: marathi
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  - config_name: nepali
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  - config_name: odia
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  - config_name: punjabi
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  - config_name: sanskrit
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  - config_name: santali
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  - config_name: sindhi
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  - config_name: tamil
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      - name: audio_filepath
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      - name: text
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      - name: duration
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      - name: lang
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      - name: samples
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      - name: verbatim
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      - name: normalized
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      - name: gender
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      - name: age_group
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      - name: job_type
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      - name: qualification
        dtype: string
      - name: area
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      - name: district
        dtype: string
      - name: state
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      - name: occupation
        dtype: string
      - name: verification_report
        dtype: string
      - name: unsanitized_verbatim
        dtype: string
      - name: unsanitized_normalized
        dtype: string
    splits:
      - name: valid
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        num_examples: 4426
      - name: train
        num_bytes: 44686288575.74
        num_examples: 353805
    download_size: 85187554733
    dataset_size: 45143870849.465996
  - config_name: telugu
    features:
      - name: audio_filepath
        dtype: audio
      - name: text
        dtype: string
      - name: duration
        dtype: float64
      - name: lang
        dtype: string
      - name: samples
        dtype: int64
      - name: verbatim
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      - name: normalized
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      - name: speaker_id
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      - name: scenario
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      - name: task_name
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      - name: gender
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      - name: age_group
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      - name: job_type
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      - name: qualification
        dtype: string
      - name: area
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      - name: district
        dtype: string
      - name: state
        dtype: string
      - name: occupation
        dtype: string
      - name: verification_report
        dtype: string
      - name: unsanitized_verbatim
        dtype: string
      - name: unsanitized_normalized
        dtype: string
    splits:
      - name: valid
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        num_examples: 2629
      - name: train
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        num_examples: 219702
    download_size: 55269638271
    dataset_size: 22950116733.359
  - config_name: urdu
    features:
      - name: audio_filepath
        dtype: audio
      - name: text
        dtype: string
      - name: duration
        dtype: float64
      - name: lang
        dtype: string
      - name: samples
        dtype: int64
      - name: verbatim
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      - name: normalized
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      - name: area
        dtype: string
      - name: district
        dtype: string
      - name: state
        dtype: string
      - name: occupation
        dtype: string
      - name: verification_report
        dtype: string
      - name: unsanitized_verbatim
        dtype: string
      - name: unsanitized_normalized
        dtype: string
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        num_examples: 2588
      - name: train
        num_bytes: 27766733703.64
        num_examples: 186535
    download_size: 49027126179
    dataset_size: 28051351711.5
configs:
  - config_name: assamese
    data_files:
      - split: valid
        path: assamese/valid-*
      - split: train
        path: assamese/train-*
  - config_name: bengali
    data_files:
      - split: valid
        path: bengali/valid-*
      - split: train
        path: bengali/train-*
  - config_name: bodo
    data_files:
      - split: valid
        path: bodo/valid-*
      - split: train
        path: bodo/train-*
  - config_name: dogri
    data_files:
      - split: valid
        path: dogri/valid-*
      - split: train
        path: dogri/train-*
  - config_name: gujarati
    data_files:
      - split: valid
        path: gujarati/valid-*
      - split: train
        path: gujarati/train-*
  - config_name: hindi
    data_files:
      - split: valid
        path: hindi/valid-*
      - split: train
        path: hindi/train-*
  - config_name: kannada
    data_files:
      - split: valid
        path: kannada/valid-*
      - split: train
        path: kannada/train-*
  - config_name: kashmiri
    data_files:
      - split: valid
        path: kashmiri/valid-*
      - split: train
        path: kashmiri/train-*
  - config_name: konkani
    data_files:
      - split: valid
        path: konkani/valid-*
      - split: train
        path: konkani/train-*
  - config_name: maithili
    data_files:
      - split: valid
        path: maithili/valid-*
      - split: train
        path: maithili/train-*
  - config_name: malayalam
    data_files:
      - split: valid
        path: malayalam/valid-*
      - split: train
        path: malayalam/train-*
  - config_name: manipuri
    data_files:
      - split: valid
        path: manipuri/valid-*
      - split: train
        path: manipuri/train-*
  - config_name: marathi
    data_files:
      - split: valid
        path: marathi/valid-*
      - split: train
        path: marathi/train-*
  - config_name: nepali
    data_files:
      - split: valid
        path: nepali/valid-*
      - split: train
        path: nepali/train-*
  - config_name: odia
    data_files:
      - split: valid
        path: odia/valid-*
      - split: train
        path: odia/train-*
  - config_name: punjabi
    data_files:
      - split: valid
        path: punjabi/valid-*
      - split: train
        path: punjabi/train-*
  - config_name: sanskrit
    data_files:
      - split: valid
        path: sanskrit/valid-*
      - split: train
        path: sanskrit/train-*
  - config_name: santali
    data_files:
      - split: valid
        path: santali/valid-*
      - split: train
        path: santali/train-*
  - config_name: sindhi
    data_files:
      - split: valid
        path: sindhi/valid-*
      - split: train
        path: sindhi/train-*
  - config_name: tamil
    data_files:
      - split: valid
        path: tamil/valid-*
      - split: train
        path: tamil/train-*
  - config_name: telugu
    data_files:
      - split: valid
        path: telugu/valid-*
      - split: train
        path: telugu/train-*
  - config_name: urdu
    data_files:
      - split: valid
        path: urdu/valid-*
      - split: train
        path: urdu/train-*

IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languages

Dataset Description

• Homepage: IndicVoices
• Repository: Github
• Paper: IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languages

Overview

INDICVOICES is a dataset of natural and spontaneous speech containing a total of 19550 hours of read (8%), extempore (76%) and conversational (15%) audio from 29K speakers covering 400+ Indian districts and 22 languages. Of these 19550 hours, 9200 hours have already been transcribed. Through this paper, we share our journey of capturing the cultural, linguistic and demographic diversity of India to create a one-of-its-kind inclusive and representative dataset. More specifically, we share an open-source blueprint for data collection at scale comprising of standardised protocols, centralised tools, a repository of engaging questions, prompts and conversation scenarios spanning multiple domains and topics of interest, quality control mechanisms, comprehensive transcription guidelines and transcription tools. We hope that this open source blueprint will serve as a comprehensive starter kit for data collection efforts in other multilingual regions of the world. Using INDICVOICES, we build IndicASR, the first ASR model to support all the 22 languages listed in the 8th schedule of the Constitution of India.

This work is funded by Bhashini, MeitY and Nilekani Philanthropies

Usage

The datasets library enables you to load and preprocess the dataset directly in Python. Ensure you have an active HuggingFace access token (obtainable from Hugging Face settings) before proceeding.

To load the dataset, run:

from datasets import load_dataset
# Load the dataset from the HuggingFace Hub
dataset = load_dataset("ai4bharat/IndicVoices","assamese",split="valid")
# Check the dataset structure
print(dataset)

You can also stream the dataset by enabling the streaming=True flag:

from datasets import load_dataset
dataset = load_dataset("ai4bharat/IndicVoices","assamese",split="valid", streaming=True)
print(next(iter(dataset)))

Citation

If you use IndicVoices in your work, please cite us:

@inproceedings{DBLP:conf/acl/JavedNGJBMSAFPR24,
  author       = {Tahir Javed and
                  Janki Nawale and
                  Eldho Ittan George and
                  Sakshi Joshi and
                  Kaushal Santosh Bhogale and
                  Deovrat Mehendale and
                  Ishvinder Virender Sethi and
                  Aparna Ananthanarayanan and
                  Hafsah Faquih and
                  Pratiti Palit and
                  Sneha Ravishankar and
                  Saranya Sukumaran and
                  Tripura Panchagnula and
                  Sunjay Murali and
                  Kunal Sharad Gandhi and
                  Ambujavalli R and
                  Manickam K. M and
                  C. Venkata Vaijayanthi and
                  Krishnan Srinivasa Raghavan Karunganni and
                  Pratyush Kumar and
                  Mitesh M. Khapra},
  title        = {IndicVoices: Towards building an Inclusive Multilingual Speech Dataset
                  for Indian Languages},
  booktitle    = {{ACL} (Findings)},
  pages        = {10740--10782},
  publisher    = {Association for Computational Linguistics},
  year         = {2024}
}

License

This dataset is released under the CC BY 4.0.

Contact

For any questions or feedback, please contact:

• Tahir Javed (tahir@cse.iitm.ac.in)
• Mitesh M. Khapra (miteshk@cse.iitm.ac.in)