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metadata
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train/*
      - split: test
        path: data/test/*
      - split: validation
        path: data/validation/*
license: cc-by-nc-sa-4.0
task_categories:
  - automatic-speech-recognition
language:
  - iru
  - ta
tags:
  - audio
  - speech
  - automatic-speech-recognition
  - asr
  - life app
  - iru
  - ta
pretty_name: Irula Translation Transcription
description: Irula_Translation_Transcription
homepage: https://lifeapp.unreal-tece.co.in/projects/D_Irula_Translation_Transcription
citation: ''

Irula Translation Transcription

Dataset Description

  • Project: Irula Translation Transcription
  • Contributors: Benakkesh, Unais, Aliza, Nithin, Gowri, Roy WorkShop003, WorkShop005, WorkShop004, Work Shop Unreal Tece, WorkShop002, BoLI, WorkShop001

About

Irula_Translation_Transcription

Tools

We employed Karya and Atekho for collecting and recording data. The complete dataset is transcribed and exported using MATra Lab. Both Atekho and MAtra Lab are part of the LiFE Suite Ecosystem, developed by Unreal Tece LLP.

Speakers

Benakkesh, Unais, Aliza, Nithin, Gowri, Roy

Annotators

WorkShop003, WorkShop005, WorkShop004, Work Shop Unreal Tece, WorkShop002, BoLI, WorkShop001

Structure

The dataset is organized by splits (e.g. train, test, validation).

Each row contains audio, audio-level metadata, prompt metadata and speaker metadata as described below:

Audio and Audio-level Metadata

  • audio: The audio file path (loaded as Audio feature in HF Datasets)
  • audio_id: Unique identifier for the audio
  • filename: Original filename
  • sentence-<SCRIPT>-transcription: Text transcription of the audio in the given script
  • speaker_id: Identifier for the speaker
  • boundaryID: Identifier for the boundary
  • start_time: Start time of the segment in seconds
  • end_time: End time of the segment in seconds

Prompt Metadata

  • 'Q_Id`: Unique identifier for the question or prompt associated with the audio (maps to the question in the LiFE Questionnaire projects and accessible through the questionnaire repo)
  • 'Domain': Domain of the audio (e.g., Agriculture, Education, General, etc.)
  • 'Elicitation_Method`: Method used to elicit the speech (e.g., Translation, Narration, etc.)
  • Target: An optional field for translation indicating the grammatical structure being targeted for elicitation using the sentence.

Speaker Metadata

  • ageGroup: Age group of the speaker (e.g., 18-30, 30-50, etc.)
  • gender: Gender of the speaker
  • educationLevel: Education level of the speaker
  • educationMediumUpto12-list: Medium of education up to 12th grade (list of comma-separated values)
  • 'educationMediumAfter12-list`: Medium of education after 12th grade (list of comma-separated values)
  • otherLanguages-list: Languages spoken by the speaker (list of comma-separated values) - this usually excludes the primary language of the dataset and is used to capture multilingualism in speakers.
  • nativeLanguage: The native language of the speaker (optional field if data is collected from non-native speakers of the language)
  • placeOfRecording: The location where the audio was recorded (optional field) or the native place of the speaker (if known)
  • typeOfplace: Whether the placeOfRecording mentioned is City, Town or Village.

Additional Metadata

  • textgrid_json: TextGrid data converted to JSON format In addition to any other metadata fields provided during upload are optionally included.

License

This work is licensed under a CC-By-NC-SA-4.0 license. This license allows reusers to distribute, remix, adapt, build upon, and incorporate into software systems, the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, build upon, or incorporate into software systems, you must license the modified material, including material generated by the software system, under identical terms, and license the software system under the GNU General Public License.

Commercial Use

If you are interested in using this dataset for commercial purposes, please contact us (contact [at] unreal-tece[dot]co[dot]in). Profits from commercial licensing will be distributed as royalties to the community members who contributed to this dataset.

Contact

For questions, issues, or contributions, open an issue on the dataset repository or contact us directly (contact [at] unreal-tece[dot]co[dot]in).