| # Multi-Accent English Speech Corpus (Augmented & Speaker-Disjoint) | |
| This dataset is a curated and augmented multi-accent English speech corpus designed for **speech recognition, accent classification, and representation learning**. | |
| It consolidates multiple open-source accent corpora, converts all audio to a unified format, applies targeted data augmentation, and exports in a tidy, Hugging Face–ready structure. | |
| --- | |
| ## ✨ Key Features | |
| - **Accents covered (12 total):** | |
| american_english, british_english, indian_english, canadian_english, australian_english, scottish_english, irish_english, new_zealand_english, northernirish, african_english, welsh_english, south_african_english | |
| - **Speaker-disjoint splits**: each speaker is assigned to exactly one split (train/validation/test). | |
| - **Augmentation strategy**: | |
| - < 2.6k samples → expanded to 5k via augmentation | |
| - 2.6k–10k samples → expanded to 10k via augmentation | |
| - > 10k samples → 50% replaced in place with augmented versions | |
| - Aug methods: time-stretch, pitch-shift, background noise injection, reverb/EQ | |
| - **Audio format (standardized)**: `.wav`, 16-bit PCM, 16 kHz sample rate, mono | |
| - **Metadata-rich**: `uid`, `text`, `accent`, `speaker_id`, `dataset`, `is_augmented`, `source_uid`, `aug_label`, `duration_s` | |
| --- | |
| ## 📂 Dataset Structure | |
| ``` | |
| hf_export/ | |
| ├── data/ | |
| │ ├── train/ | |
| │ │ ├── 0000/uid.wav | |
| │ │ └── ... | |
| │ ├── validation/ | |
| │ └── test/ | |
| ├── metadata/ | |
| │ ├── train.parquet | |
| │ ├── validation.parquet | |
| │ └── test.parquet | |
| ├── SPLIT_REPORT.md | |
| ├── QA_REPORT.md | |
| ├── splits_by_speaker.csv | |
| └── README.md | |
| ``` | |
| --- | |
| ## 🗂 Metadata Schema | |
| | Column | Type | Description | | |
| |--------------|----------|-------------| | |
| | `uid` | string | Unique ID per sample | | |
| | `path` | string | Relative path to the `.wav` file | | |
| | `text` | string | Transcript | | |
| | `accent` | string | One of 17 whitelisted accents | | |
| | `speaker_id` | string | Unique speaker ID (dataset-prefixed) | | |
| | `dataset` | string | Source dataset (cv, vctk, accentdb, etc.) | | |
| | `is_augmented` | bool | True if augmented | | |
| | `source_uid` | string | UID of the original sample (for augmented rows) | | |
| | `aug_label` | string | Applied augmentation method (e.g., `pitch:+1.2`) | | |
| | `duration_s` | float32 | Duration in seconds | | |
| Note: for accents with over 10k samples, is_augmented is false even though there's augmentation for half of their size. Use random sampling for these accents. | |
| --- | |
| ## 📊 Splitting Strategy | |
| - **Ratios**: 78% train, 11% validation, 11% test | |
| - **Speaker-disjoint**: a speaker appears in only one split | |
| - **Accent-aware**: splits preserve global accent proportions | |
| - **Dataset balance**: allocator prefers splits underrepresented for a dataset | |
| - **Augmentation inheritance**: augmented samples inherit the split of their source speaker | |
| --- | |
| ## ✅ Preflight Validations | |
| Checks applied before release: | |
| - Unique `uid` values | |
| - All files exist and are readable | |
| - Format: 16kHz / mono / PCM_16 | |
| - `accent` ∈ whitelist (17) | |
| - Transcripts non-empty | |
| - Augmented samples link back to valid originals | |
| - Duration bounds: 0.2s–30s (flagged outliers) | |
| - Speaker-disjointness across splits | |
| - Accent & dataset distributions close to global ratios | |
| - Duplicate detection (duration+text fingerprint) | |
| Reports: | |
| - **SPLIT_REPORT.md**: speaker allocation, accent/dataset balance | |
| - **QA_REPORT.md**: split sizes, duration anomalies, duplicate candidates | |
| --- | |
| ## 🔎 Example Usage | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("cagatayn/multi_accent_speech", split="train") | |
| print(ds[0]) | |
| # { | |
| # 'uid': 'abc123', | |
| # 'path': 'data/train/0000/abc123.wav', | |
| # 'text': "it's the philosophy that guarantees everyone's freedom", | |
| # 'accent': 'american_english', | |
| # 'speaker_id': 'cv_sample-000031', | |
| # 'dataset': 'cv', | |
| # 'is_augmented': False, | |
| # 'source_uid': '', | |
| # 'aug_label': '', | |
| # 'duration_s': 3.21, | |
| # 'audio': {'path': 'data/train/0000/abc123.wav', 'array': ..., 'sampling_rate': 16000} | |
| # } | |
| ``` | |
| --- | |
| ## 📜 License | |
| - Audio/data sourced from **Common Voice, VCTK, L2 Arctic, Speech Accent Archive, AccentDB**. | |
| - Augmented versions generated as derivative works. | |
| - Redistribution follows the most restrictive upstream license. Please review original dataset terms before commercial use. | |
| --- | |
| ## 🙏 Acknowledgments | |
| - Mozilla [Common Voice](https://commonvoice.mozilla.org/) | |
| - [VCTK Corpus](https://datashare.ed.ac.uk/handle/10283/3443) | |
| - [Speech Accent Archive](https://accent.gmu.edu/) | |
| - [AccentDB](https://github.com/AI4Bharat/AccentDB) | |
| - [L2-ARCTIC Corpus](https://psi.engr.tamu.edu/l2-arctic-corpus/) | |
| --- | |