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README.md

@@ -1,3 +1,162 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+  - automatic-speech-recognition
+language:
+  - en
+tags:
+  - audio
+  - speech
+  - whisper
+  - asr
+  - stt
+  - wpm
+  - background-noise
+  - speech-recognition
+  - evaluation
+pretty_name: ASR WPM and Background Noise Evaluation Dataset
+size_categories:
+  - n<1K
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: metadata.jsonl
+    default: true
+dataset_info:
+  features:
+    - name: id
+      dtype: string
+    - name: audio
+      dtype: audio
+    - name: sample
+      dtype: string
+    - name: sample_file
+      dtype: string
+    - name: word_count
+      dtype: int32
+    - name: duration_seconds
+      dtype: float32
+    - name: recorded_at
+      dtype: string
+    - name: annotations
+      struct:
+        - name: pace
+          dtype: string
+        - name: mic_distance
+          dtype: string
+        - name: background_noise
+          dtype: string
+        - name: notes
+          dtype: string
+    - name: equipment
+      struct:
+        - name: microphone
+          dtype: string
+        - name: sample_rate
+          dtype: int32
+        - name: channels
+          dtype: int32
+---
+
+# ASR WPM and Background Noise Evaluation Dataset
+
+A dataset of annotated audio recordings for evaluating how different factors affect Whisper (and other ASR/STT systems) transcription accuracy.
+
+## Purpose
+
+This dataset provides controlled audio samples with annotations to evaluate ASR performance across:
+
+- **Speaking pace** (fast, normal, slow, mumbled, whispered, weird voices)
+- **Background noise** (cafe, music, conversations in various languages, traffic, sirens, etc.)
+- **Microphone distance** (close, normal, far)
+
+## Dataset Structure
+
+Each sample includes:
+- A WAV audio file (16kHz mono)
+- Metadata with annotations describing recording conditions
+
+### Features
+
+| Feature | Type | Description |
+|---------|------|-------------|
+| `id` | string | 4-character hex identifier |
+| `audio` | audio | Path to WAV file |
+| `sample` | string | Text sample identifier |
+| `sample_file` | string | Source text filename |
+| `word_count` | int | Number of words in the sample |
+| `duration_seconds` | float | Recording duration |
+| `recorded_at` | string | Timestamp (YYYYMMDD_HHMMSS) |
+| `annotations.pace` | string | Speaking pace category |
+| `annotations.mic_distance` | string | Microphone distance |
+| `annotations.background_noise` | string | Background noise type |
+| `annotations.notes` | string | Additional notes |
+| `equipment.microphone` | string | Recording device |
+| `equipment.sample_rate` | int | Audio sample rate (16000) |
+| `equipment.channels` | int | Audio channels (1 = mono) |
+
+### Annotation Categories
+
+**Speaking Pace:**
+- `fast` - As fast as possible
+- `quick` - Quicker than normal
+- `normal` - Normal/conversational
+- `slow` - Deliberately slow
+- `whispered` - Whispered speech
+- `loud` - Louder than normal
+- `weird_voices` - Altered/unusual voice patterns
+
+**Microphone Distance:**
+- `close` - Less than 6 inches
+- `normal` - 6-12 inches
+- `far` - Greater than 12 inches
+
+**Background Noise:**
+- `none` - Silence
+- `cafe` - Coffee shop ambience
+- `music` - Background music (various genres)
+- `convo_same` - Same-language conversation
+- `convo_other` - Other-language conversation (Spanish, Arabic, Korean, Japanese, Mandarin, Cantonese, Irish English)
+- `convo_mixed` - Mixed language babble
+- `transit` - Airport/transportation sounds
+- `honking` - Traffic/horns
+- `siren` - Emergency vehicle sirens
+- `dogs` - Dog barking
+- `baby` - Baby sounds
+
+## Audio Specifications
+
+- **Format:** WAV
+- **Sample Rate:** 16kHz
+- **Channels:** Mono
+- **Equipment:** Samson Q2U USB Microphone
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("danielrosehill/ASR-WPM-And-Background-Noise-Eval")
+
+# Access audio and metadata
+for sample in dataset["train"]:
+    audio = sample["audio"]
+    pace = sample["annotations"]["pace"]
+    noise = sample["annotations"]["background_noise"]
+```
+
+## Use Cases
+
+- Benchmarking ASR/STT models under varying conditions
+- Evaluating robustness to background noise
+- Testing speech recognition at different speaking rates
+- Comparing transcription accuracy across challenging audio scenarios
+
+## Source
+
+Recording tools and methodology: [Whisper-WPM-Eval](https://github.com/danielrosehill/Whisper-WPM-Eval)
+
+## License
+
+MIT