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README.md

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 license: apache-2.0
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+# Dataset Card for KasaSpeech
+
+## Dataset Summary
+
+**KasaSpeech** is a large-scale English–Twi code-switching speech dataset designed to support the development of speech technologies for low-resource African languages. The dataset comprises **54,855** transcribed speech recordings collected from speakers across Ghana, capturing natural code-switching between English and Twi in conversational and prompted speech.
+
+With over **95 hours** of annotated audio, KasaSpeech serves as a benchmark for multilingual and code-switching Automatic Speech Recognition (ASR), speech representation learning, and language technology research for African languages.
+
+---
+
+## Supported Tasks
+
+KasaSpeech is suitable for:
+
+* Automatic Speech Recognition (ASR)
+* Code-switching speech recognition
+* Multilingual speech modeling
+* Speech representation learning
+* Speech foundation model fine-tuning and evaluation
+* African language speech technology research
+
+
+## Dataset Structure
+
+### Data Splits
+
+| Split      |    Samples |        Duration |
+| ---------- | ---------: | --------------: |
+| Train      |     50,965 |     83.94 hours |
+| Validation |      2,159 |      6.80 hours |
+| Test       |      1,731 |      4.84 hours |
+| **Total**  | **54,855** | **95.58 hours** |
+
+
+### Data Fields
+
+Each example contains the following fields:
+
+| Field        | Type      | Description                                          |
+| ------------ | --------- | ---------------------------------------------------- |
+| `speaker_id` | `string`  | Anonymous speaker identifier                         |
+| `age_range`  | `string`  | Speaker age group                                    |
+| `gender`     | `string`  | Speaker gender                                       |
+| `prompt_set` | `string`  | Prompt category used during recording                |
+| `transcript` | `string`  | Human-annotated English–Twi code-switched transcript |
+| `duration`   | `float32` | Audio duration in seconds                            |
+| `split`      | `string`  | Dataset split (`train`, `validation`, or `test`)     |
+| `audio`      | `Audio`   | Speech recording                                     |
+| `file_name`  | `string`  | Original audio filename                              |
+| `error`      | `string`  | Optional annotation or recording error label         |
+
+
+## Example
+
+```python
+from datasets import load_dataset, Audio
+
+dataset = load_dataset(
+    "Kennethdot/Ghana_English-Twi_Code_switching_ASR",
+    split="train"
+)
+
+dataset = dataset.cast_column(
+    "audio",
+    Audio(sampling_rate=16000)
+)
+
+sample = dataset[0]
+
+print(sample["transcript"])
+print(sample["audio"]["sampling_rate"])
+```
+
+Example transcript:
+
+```text
+Me phone no a-crack-i, henfa na mɛtumi a-fix-i screen no?
+```
+
+---
+
+## Dataset Creation
+
+### Collection Process
+
+Speech recordings were voluntarily contributed by participants using a custom data collection platform. Speakers were presented with prompts designed to encourage natural English–Twi code-switching while covering a broad range of everyday topics and communication scenarios.
+
+### Annotation Process
+
+All recordings were manually transcribed following standardized annotation guidelines developed for English–Twi code-switched speech. Multiple quality assurance steps were performed to improve transcription consistency and remove corrupted or invalid recordings.
+
+### Speaker Information
+
+The dataset includes recordings from speakers spanning multiple age groups and genders. Speaker identities have been anonymized using unique identifiers.
+
+---
+
+## Dataset Characteristics
+
+* **Total recordings:** 54,855
+* **Total duration:** 95.58 hours
+* **Languages:** English, Twi, and English–Twi code-switching
+* **Sampling rate:** 48 kHz (can be resampled to 16 kHz for model training)
+* **Recording style:** Prompted, natural code-switched speech
+* **Transcriptions:** Human-annotated
+
+---
+
+## Intended Uses
+
+KasaSpeech is intended to support research in:
+
+* Automatic Speech Recognition (ASR)
+* Code-switching speech modeling
+* Low-resource multilingual speech processing
+* African language technologies
+* Benchmarking multilingual speech models
+* Fine-tuning and evaluating speech foundation models such as Whisper, wav2vec 2.0, MMS, and SeamlessM4T
+
+---
+
+## Limitations
+
+* Demographic representation may not be perfectly balanced across speaker groups.
+* Recording conditions vary across devices and environments.
+* The dataset primarily reflects Ghanaian English–Twi code-switching and may not generalize to all Akan dialects or other multilingual contexts.
+* Although carefully curated, minor transcription inconsistencies may remain.
+
+---
+
+## Citation
+
+If you use **KasaSpeech** in your work, please cite:
+
+```bibtex
+@dataset{kasaspeech2026,
+  title={KasaSpeech: A Large-Scale English--Twi Code-Switching Speech Dataset},
+  author={Dotse, Kenneth},
+  year={2026},
+  url={https://huggingface.co/datasets/Kennethdot/Ghana_English-Twi_Code_switching_ASR}
+}
+```
+
+---
+
+## Licensing
+
+Please refer to the dataset repository for the applicable license.
+
+---
+
+## Contact
+
+For questions, bug reports, or collaboration opportunities, please open a discussion on the Hugging Face dataset page. Contributions, feedback, and research collaborations are welcome.