Datasets:
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README.md
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splits:
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- name: train
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num_bytes: 275284152
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num_examples: 1500
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download_size: 263378447
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dataset_size: 275284152
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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dtype: string
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splits:
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- name: train
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num_bytes: 275284152
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num_examples: 1500
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download_size: 263378447
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dataset_size: 275284152
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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license: cc0-1.0
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task_categories:
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- automatic-speech-recognition
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language:
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- sw
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tags:
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- swahili
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- speech
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- kenyan
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- audio
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- common-voice
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- automatic-speech-recognition
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pretty_name: 'Common Voice 17.0 (Swahili, Kenyan Sample) '
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size_categories:
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- 1K<n<10K
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---
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# Common Voice 17.0 — Swahili (Kenyan Sample)
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This dataset is a **filtered sample** of the [Mozilla Common Voice 17.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_17_0) corpus, focusing on **Swahili (sw)** speech with **Kenyan voices**.
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It has been subsetted for experimentation and prototyping in **ASR (Automatic Speech Recognition)** models targeting **speech-impaired users** in Kenya, covering **Kenyan English** and **Kiswahili**.
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---
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## Dataset Summary
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- **Language**: Kiswahili (Swahili, `sw`)
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- **Accent/Region**: Kenyan speakers
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- **Domain**: Conversational, general-purpose
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- **Source**: Mozilla Common Voice v17.0
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- **License**: CC0 1.0 (public domain)
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This dataset contains audio files and their corresponding transcriptions.
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Each entry includes:
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- `audio`: Audio array & path
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- `sentence`: Transcription text
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- `gender`, `age`, `accent` (where available)
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---
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## Intended Use
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This sample dataset is intended for:
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- Training and fine-tuning **speech-to-text (ASR)** systems for Kiswahili
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- Research on **Kenyan accents** in speech technology
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- Prototyping models for **speech accessibility tools**
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It is **not a full dataset**, but a filtered subset suitable for testing and demonstrations.
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---
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## Usage Example
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```python
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from datasets import load_dataset
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# Load dataset (requires auth if private)
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ds = load_dataset("Veronica1NW/cv17_sw_kenyan_sample", use_auth_token=True)
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print(ds)
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print(ds["train"][0])
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@misc{commonvoice,
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title = {Mozilla Common Voice},
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howpublished = {https://commonvoice.mozilla.org},
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year = {2017--2025}
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}
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