README.md

metadata

dataset_info:
  features:
    - name: recorder_uuid
      dtype: string
    - name: type
      dtype: string
    - name: file_name
      dtype: string
    - name: full_path
      dtype: string
    - name: domain
      dtype: string
    - name: topic
      dtype: string
    - name: scenario
      dtype: string
    - name: text
      dtype: string
    - name: duration
      dtype: float64
    - name: size_bytes
      dtype: int64
    - name: microphone_device_id
      dtype: string
    - name: microphone_label
      dtype: string
    - name: audio
      dtype: audio
    - name: __index_level_0__
      dtype: int64
  splits:
    - name: train
      num_bytes: 227974446
      num_examples: 100
  download_size: 211404519
  dataset_size: 227974446
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - automatic-speech-recognition
language:
  - st
tags:
  - anv
pretty_name: anv-za-sot-1h-sample-dataset
size_categories:
  - 1K<n<10K
extra_gated_prompt: >-
  I agree to use this data with the license conditions and use restrictions. You
  agree to NOT USE the data for creating models for any form of text-to-speech
  (TTS), voice cloning, voice synthesis, or any technology intended to replicate
  or generate human voices.
extra_gated_fields:
  Company: text
  Country: country
  Specific date: date_picker
  I want to use this model for:
    type: select
    options:
      - Research
      - Education
      - label: Other
        value: other
  I agree to use this data with the license conditions and use restrictions: checkbox

Sesotho Sample Dataset - Next Voices-ZA (South Africa) - Multilingual Speech Dataset - Sesotho

This dataset includes scripted and unscripted speech across various domains such as agriculture, health, finance, sports, transport, culture, society and general topics. It is primarily designed for automatic speech recognition (ASR).

Use Restriction:

The persons whose voices are included in this dataset, and the creators and owners of this dataset* do not give consent in any manner or form to, and strictly prohibit any use of this dataset for any form of text-to-speech (TTS), voice cloning, voice synthesis, or any technology or activity intended to replicate, mimic or generate human voices or any technology or activity resulting in the replication, mimicry or generation of human voices.

This dataset includes scripted and unscripted speech across various domains such as agriculture, health, finance, sports, transport, culture, society, and general topics. It is primarily designed for use in automatic speech recognition (ASR) tasks.

Use of this dataset for any form of text-to-speech (TTS), voice cloning, voice synthesis, or any technology intended to replicate or generate human voices is strictly prohibited.

These restrictions are in place until further notice.

Folder structure

The dataset is organised hierarchically as follows:

Folder Structure

ANV-ZA-SOT-1h/
├── sot/                  # Folder for Sesotho
│   ├── recorder_uuid/    # Contains all audio files
│   │   ├── recording-1731053452.wav
│   │   ├── ...
│   ├── transcripts.csv    # Contains transcripts of all audio recordings
│   ├── meta.csv          # Contains additional metadata
├── README.md             # Description of the dataset

Data overview

Audio

• Format: 16-bit PCM WAV
• Sample rate: 48kHz

Transcriptions

• Provided in transcript.csv with fields:   - file_name: Name of the audio file.   - transcript: Text transcription of the audio.   - duration: Duration of the recording in seconds.   - type: Scripted or unscripted.

Metadata

• Provided in meta.csv with fields such as:   - recorder_uuid: Unique speaker identifier.   - age_range, gender

Citation Information

Bibtex Reference (last updated 10/02/2025)

@dataset{marivate_2024_14336304,
  author       = {Marivate, Vukosi and
                  Olaleye, Kayode and
                  Mundia, Sitwala and
                  van Wyk, Nia Zion and
                  Bakainaga, Andinda and
                  Morrissey, Graham and
                  Dunbar, Dale and
                  Smit, Francois and
                  Mogale, Hope Tsholofelo and Okorie, Chijioke},
  title        = {ANV-SOT-Sample-1: Sesotho Sample Dataset - Next
                   Voices-ZA (South Africa)
                  },
  month        = dec,
  year         = 2024,
  publisher    = {Zenodo},
  version      = {0.0.2},
  doi          = {10.5281/zenodo.14336304},
  url          = {https://doi.org/10.5281/zenodo.14336304},
}