| | --- |
| | license: cc-by-4.0 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: test |
| | path: data/test-* |
| | dataset_info: |
| | features: |
| | - name: audio |
| | dtype: audio |
| | - name: duration |
| | dtype: float64 |
| | - name: reference |
| | dtype: string |
| | - name: RobotsMali/stt-bm-quartznet15x5-v0 |
| | dtype: string |
| | - name: RobotsMali/stt-bm-quartznet15x5-v1 |
| | dtype: string |
| | - name: RobotsMali/soloba-ctc-0.6b-v0 |
| | dtype: string |
| | - name: RobotsMali/soloba-ctc-0.6b-v1 |
| | dtype: string |
| | - name: RobotsMali/soloni-114m-tdt-ctc-v0 |
| | dtype: string |
| | - name: RobotsMali/soloni-114m-tdt-ctc-v1 |
| | dtype: string |
| | - name: RobotsMali/stt-bm-quartznet15x5-v2 |
| | dtype: string |
| | - name: soloni-114m-tdt-ctc-v2 |
| | dtype: string |
| | splits: |
| | - name: test |
| | num_bytes: 20690456 |
| | num_examples: 45 |
| | download_size: 19975985 |
| | dataset_size: 20690456 |
| | task_categories: |
| | - automatic-speech-recognition |
| | language: |
| | - bm |
| | tags: |
| | - speech |
| | - asr |
| | - bambara |
| | - low-resource |
| | --- |
| | # Nyana-Eval Dataset |
| |
|
| | ## Dataset Description |
| |
|
| | **Nyana-Eval** is a compact, stratified evaluation subset for benchmarking Automatic Speech Recognition (ASR) models in Bambara. It consists of **45 audio recordings** totaling approximately **3.03 minutes**, carefully selected to represent real-world linguistic and acoustic challenges in low-resource Bambara speech. This dataset is derived from the larger [RobotsMali/Bam_ASR_Eval_500](https://huggingface.co/datasets/RobotsMali/Bam_ASR_Eval_500) corpus and is optimized for quick, reproducible human evaluation. |
| |
|
| | Nyana-Eval is ideal for: |
| | - Rapid evaluation of Bambara ASR models (e.g., WER/CER computation on diverse conditions). |
| | - Human-assisted qualitative analysis (e.g., semantic fidelity, code-switching handling). |
| | - Testing models on low-resource settings gaps: dialectal variations, noise, proper names, and code-mixing with French. |
| |
|
| | **Key Statistics**: |
| | - **Total Samples**: 45 (balanced: 15 per source subset). |
| | - **Total Duration**: ~3.03 minutes (average ~4.0 seconds per sample). |
| | - **Audio Format**: Mono-channel WAV files at 16 or 44.1k kHz sampling rate. |
| | - **Languages**: Primary: Bambara (Bamana); Secondary: French code-switching (~15% of samples). |
| | - **License**: CC-BY-4.0 License (open for research, commercial use with attribution). |
| |
|
| | Compiled by Robots Mali AI4D Lab, this dataset powers the human-comparative analysis in the [Bambara ASR Models Evaluation Report]. |
| |
|
| | ## Dataset Structure |
| |
|
| | Nyana-Eval is a single-split dataset (default: `test`), with each entry including raw audio, duration, transcriptions (reference) and models transcriptions. |
| |
|
| | ### Features/Columns |
| |
|
| | | Column | Type | Description | Example Value | |
| | |-----------------|----------|-----------------------------------------------------------------------------|---------------| |
| | | `audio` | Audio | Raw audio waveform (array + sampling rate: 16 or 44.1k kHz) or file path. | `{"path": "1.1.wav", "array": [...], "sampling_rate": 16000}` | |
| | | `duration` | Float64 | Length of the audio clip in seconds (range: 0.62s – 15s). | 3.45 | |
| | | `references` | String | Bambara text | "nɔgɔ ye a ka tɔɔrɔ ye" | |
| | | '8 * models transcriptions' | String | ASR provised transcriptions | | |
| |
|
| | ### Splits |
| | - **Default Split**: Full 45 samples (`test` for evaluation). |
| | - **Subsets by Source**: Balanced 15 samples each from the three parent subsets (see Sources below). |
| |
|
| | To load in Python (via Hugging Face Datasets): |
| | ```python |
| | from datasets import load_dataset |
| | dataset = load_dataset("RobotsMali/nyana-eval", split="test") |
| | print(len(dataset)) # Output: 45 |
| | print(dataset[0]) # Example: {'audio': ..., 'duration': 3.45, 'transcription': 'adama dusukasilen ye a sigi'} |
| | ``` |
| |
|
| | ## Sources and Compilation |
| |
|
| | Nyana-Eval is a **balanced subsample (15 per subset)** from the full 500-sample [RobotsMali/Bam_ASR_Eval_500](https://huggingface.co/datasets/RobotsMali/Bam_ASR_Eval_500) corpus (~36.69 minutes total). Selection criteria ensured diversity: voice variety (age/gender/accents), acoustic challenges (noise/volume/overlaps), and linguistic phenomena (code-switching, proper names etc.) |
| |
|
| | **Parent Subsets Breakdown** (15 samples each in Nyana-Eval): |
| | - **Ref. 1: RobotsMali/kunkado (Hugging Face)** – 15 audios (~1.96 minutes scaled). |
| | Semi-supervised interviews and spontaneous discourse. Source: [RobotsMali/kunkado](https://huggingface.co/datasets/RobotsMali/kunkado). Focus: Dialectal variations and natural flow. |
| |
|
| | - **Ref. 2: jeli-ASR street interviews subset** – 30 audios (~1.85 minutes). |
| | Street interviews Subset from the jeli-asr project. Source: [jeli-asr](https://github.com/robotsmali-ai/jeli-asr/) |
| |
|
| | - **Ref. 3: Readings of Excerpts from An Bɛ Kalan app (RobotsMali)** – 220 audios (~20.06 minutes). |
| | User-generated readings and interactions from the mobile app for Bambara learning, captures learner speech with occasional errors or pauses. source: [RobotsMali-AI/an-be-kalan](https://github.com/Robotsmali-ai/an-be-kalan) |
| |
|
| | ## Metadata |
| |
|
| | ### General Metadata |
| | - **Creator**: Robots Mali AI4D Lab |
| | - **Version**: 1.0 (November 2025). |
| | - **Creation Date**: Derived November 2025 from Bam_ASR_Eval_500. |
| | - **Update Frequency**: Static (expansions via parent dataset). |
| | - **Download Size**: ~25 MB (audios + metadata). |
| | - **Ethical Notes**: Ethically sourced/anonymized; focuses on public-domain cultural speech. For research; cite Robots Mali. |
| | |
| | ### Challenges Represented: |
| | - Code-switching: samples (e.g., "Segou ville"). |
| | - Proper names (e.g., "Sunjata," "Traoré"). |
| | - Noise/Overlaps: (e.g., low-volume interviews, multi-speaker). |
| | |
| | ## Related Resources |
| | - **Parent Dataset**: [RobotsMali/Bam_ASR_Eval_500](https://huggingface.co/datasets/RobotsMali/Bam_ASR_Eval_500) (full 500 samples). |
| | - **Models**: Test with [RobotsMali ASR models](https://huggingface.co/RobotsMali/models) |
| | - **App**: Collect similar data via [An Bɛ Kalan](https://play.google.com/store/apps/details?id=org.robotsmali.literacy_app). |
| | |
| | This README is self-contained; explore the attached report PDF for detailed human annotations and model rankings on these exact 45 samples! |
| | |
| | ## Citation |
| | |
| | ```bibtex |
| | @dataset{robotsmali_nyana_eval_2025, |
| | author = {RobotsMali AI4D Lab}, |
| | title = {Nyana-Eval: 45-sample Human-Evaluated Bambara ASR Test Set}, |
| | year = {2025}, |
| | url = {https://huggingface.co/datasets/RobotsMali/nyana-eval}, |
| | note = {Stratified subset of Bam_ASR_Eva_500 used for human + WER evaluation} |
| | } |
