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resproj007/torgo_dysarthric_female

Torgo Dysarthric Female Dataset Overview This dataset contains dysarthric speech samples from a female speaker (F04) in the TORGO corpus, prepared for pathological speech synthesis research. Speaker Information: Speaker ID: F04 Corpus: TORGO Gender: Female Speech Status: Dysarthric Dataset Statistics Total Samples: 670 Total Duration: 0.60 hours Sampling Rate: 24,000 Hz Format: Audio arrays with transcriptions Training Split… See the full description on the dataset page: https://huggingface.co/datasets/resproj007/torgo_dysarthric_female.

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Torgo Dysarthric Female Dataset

Overview

This dataset contains dysarthric speech samples from a female speaker (F04) in the TORGO corpus, prepared for pathological speech synthesis research.

Speaker Information:

  • —Speaker ID: F04
  • —Corpus: TORGO
  • —Gender: Female
  • —Speech Status: Dysarthric

Dataset Statistics

  • —Total Samples: 670
  • —Total Duration: 0.60 hours
  • —Sampling Rate: 24,000 Hz
  • —Format: Audio arrays with transcriptions

Training Split

  • —Samples: 600
  • —Duration: 0.54 hours
  • —Avg Duration: 3.3s
  • —Duration Range: 0.8s - 10.2s
  • —Avg Text Length: 13 characters

Test Split

  • —Samples: 70
  • —Duration: 0.06 hours
  • —Avg Duration: 3.3s
  • —Duration Range: 0.6s - 10.3s
  • —Avg Text Length: 12 characters

Loading the Dataset

python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("your-username/torgo_dysarthric_female")

# Access train and test splits
train_data = dataset['train']
test_data = dataset['test']

# Each sample contains:
# - 'audio': {'array': numpy_array, 'sampling_rate': 24000}
# - 'text': str (normalized transcription)

# Example usage
sample = train_data[0]
audio_array = sample['audio']['array']
transcription = sample['text']
sampling_rate = sample['audio']['sampling_rate']

Direct Training with Transformers

python
from transformers import Trainer
from datasets import load_dataset

# Load and use directly with Trainer (no preprocessing needed)
dataset = load_dataset("your-username/torgo_dysarthric_female")
trainer = Trainer(
    train_dataset=dataset['train'],
    eval_dataset=dataset['test'],
    # ... other trainer arguments
)