audio
audioduration (s) 0.9
17.7
| text
stringlengths 2
77
|
|---|---|
six
|
|
hair
|
|
the quick brown fox jumps over the lazy dog
|
|
are your grades higher or lower than nancy's
|
|
everything went real smooth the sheriff said
|
|
bread
|
|
mere
|
|
brawn
|
|
tear
|
|
nothing has been done yet to take advantage of the enabling legislation
|
|
shy
|
|
one validated acts of school districts
|
|
lip
|
|
slay
|
|
hat
|
|
bright sunshine shimmers on the ocean
|
|
group
|
|
suit
|
|
we're
|
|
goat
|
|
i was conscious all the time
|
|
pile
|
|
blow
|
|
torn
|
|
the islands are sparsely populated
|
|
everything went real smooth the sheriff said
|
|
sip
|
|
goat
|
|
sheet
|
|
sleep
|
|
fear
|
|
warm
|
|
steer
|
|
knew
|
|
go
|
|
ate
|
|
tell
|
|
their house is grey and white
|
|
witty
|
|
pit
|
|
you wished to know all about my grandfather
|
|
lick
|
|
spit
|
|
i can
|
|
bloat
|
|
toot
|
|
much
|
|
feed
|
|
cycle
|
|
hem
|
|
are your grades higher or lower than nancy's
|
|
steer
|
|
i expect we'll bounce back this week
|
|
foxtrot
|
|
chop
|
|
store
|
|
jungle
|
|
yes
|
|
knot
|
|
brought
|
|
chop
|
|
slip
|
|
bat
|
|
cart
|
|
four
|
|
the job provides many benefits
|
|
nine
|
|
jane may earn more money by working hard
|
|
mike
|
|
know
|
|
spain
|
|
leak
|
|
charlie
|
|
reek
|
|
i just try to do my best
|
|
him
|
|
being able to dance can help too
|
|
this is not a program of socialized medicine
|
|
pay
|
|
witch
|
|
dark
|
|
well he is nearly ninetythree years old
|
|
at
|
|
why yell or worry over silly items
|
|
if you destroy confidence in banks you do something to the economy he said
|
|
tip
|
|
students watched as he got out
|
|
why yell or worry over silly items
|
|
the books are very expensive
|
|
hill
|
|
the misguided souls have lost their way
|
|
swarm
|
|
feed
|
|
zero
|
|
gadget
|
|
share
|
|
where were you while we were away
|
|
part
|
|
store
|
|
stick
|
End of preview. Expand
in Data Studio
Torgo Dysarthric Male Dataset (Updated)
Overview
This dataset contains dysarthric speech samples from a male speaker (M02) in the TORGO corpus, prepared for pathological speech synthesis research.
Speaker Information:
- Speaker ID: M02
- Corpus: TORGO
- Gender: Male
- Speech Status: Dysarthric
Dataset Statistics
- Total Samples: 770
- Total Duration: 0.79 hours
- Sampling Rate: 24,000 Hz
- Format: Audio arrays with transcriptions
Training Split
- Samples: 700
- Duration: 0.72 hours
- Avg Duration: 3.7s
- Duration Range: 0.9s - 17.7s
- Avg Text Length: 12 characters
Test Split
- Samples: 70
- Duration: 0.07 hours
- Avg Duration: 3.5s
- Duration Range: 1.2s - 15.9s
- Avg Text Length: 12 characters
Loading the Dataset
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("your-username/torgo_dysarthric_male")
# 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
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_male")
trainer = Trainer(
train_dataset=dataset['train'],
eval_dataset=dataset['test'],
# ... other trainer arguments
)
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