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README.md

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+---
+dataset_info:
+  features:
+  - name: ID
+    dtype: string
+  - name: speaker_id
+    dtype: string
+  - name: Language
+    dtype: string
+  - name: audio
+    dtype: 
+      audio:
+        sampling_rate: 16000
+  - name: transcript
+    dtype: string
+  - name: length
+    dtype: float32
+  - name: dataset_name
+    dtype: string
+  - name: confidence_score
+    dtype: float64
+  splits:
+  - name: train
+    num_examples: 50
+  download_size: 0
+  dataset_size: 0
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train/*.parquet
+---
+
+# Thanarit/Thai-Voice
+
+Combined Thai audio dataset from multiple sources
+
+## Dataset Details
+
+- **Total samples**: 50
+- **Total duration**: 0.06 hours
+- **Language**: Thai (th)
+- **Audio format**: 16kHz mono WAV
+- **Volume normalization**: -20dB
+
+## Sources
+
+Processed 1 datasets in streaming mode
+
+## Source Datasets
+
+1. **GigaSpeech2**: Large-scale multilingual speech corpus
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load with streaming to avoid downloading everything
+dataset = load_dataset("Thanarit/Thai-Voice-Test-Final", streaming=True)
+
+# Iterate through samples
+for sample in dataset['train']:
+    print(sample['ID'], sample['transcript'][:50])
+    # Process audio: sample['audio']
+    break
+```
+
+## Schema
+
+- `ID`: Unique identifier (S1, S2, S3, ...)
+- `speaker_id`: Speaker identifier (SPK_00001, SPK_00002, ...)
+- `Language`: Language code (always "th" for Thai)
+- `audio`: Audio data with 16kHz sampling rate
+- `transcript`: Text transcript of the audio
+- `length`: Duration in seconds
+- `dataset_name`: Source dataset name (e.g., "GigaSpeech2", "ProcessedVoiceTH", "MozillaCommonVoice")
+- `confidence_score`: Confidence score of the transcript (0.0-1.0)
+  - 1.0: Original transcript from source dataset
+  - <1.0: STT-generated transcript
+  - 0.0: Fallback transcript (e.g., [NO_TRANSCRIPT])
+
+## Processing Details
+
+This dataset was created using streaming processing to handle large-scale data without requiring full downloads.
+Audio has been standardized to 16kHz mono with -20dB volume normalization.