Datasets:

Modalities:
Audio
Text
Formats:
parquet
Languages:
Kazakh
DOI:
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Dask
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Kazakh Speech Dataset (KSD)

1. Dataset Summary

  • Purpose: High-quality, open-source Kazakh speech dataset for Automatic Speech Recognition (ASR) system development.
  • Developed by: Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University.
  • Total Duration: 554 hours of recorded speech.
  • Total Number of Speakers: 873
  • Average Sentences per Speaker: 250 sentences (utterances).
  • Total Utterances: 204,250
  • File Format: .wav
  • Audio Characteristics:
    • Sample Rates: 16 kHz or 22 kHz
    • Bit Depth: 16-bit
    • Channels: Mono

2. Corpus Features

  • Speaker Diversity: Speakers from diverse regions, age groups, and genders.
  • Recording Devices: Recorded using mobile devices (iOS and Android).
  • Transcription Quality: Verified by native Kazakh speakers for accuracy.

3. Applications

  • Primary Use Case: Automatic Speech Recognition (ASR) system training.
  • Additional Use Cases:
    • Speech-to-text systems.
    • Voice-activated assistants.
    • Speaker identification.
    • Linguistic research on Kazakh phonetics and dialects.

4. Technical Characteristics

  • File Format: .wav
  • Sample Rates: 16 kHz, 22 kHz, or 44 kHz.
  • Bit Depth: 16-bit
  • Channels: Mono
  • Recording Devices: Mobile devices (iOS, Android).

5. Citation

If you use this dataset, please cite it as follows:

@article{kadyrbek2023ksd,
  author = {Kadyrbek, N.; Mansurova, M.; Shomanov, A.; Makharova, G.},
  title = {The Development of a Kazakh Speech Recognition Model Using a Convolutional Neural Network with Fixed Character Level Filters},
  journal = {Big Data and Cognitive Computing},
  year = {2023},
  volume = {7},
  number = {3},
  pages = {132},
  doi = {https://doi.org/10.3390/bdcc7030132}
}
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