Datasets:

Codyfederer
/

test3434234

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
audio: struct<bytes: binary, path: string>
  child 0, bytes: binary
  child 1, path: string
text: string
speaker_id: string
language: string
emotion: string
original_dataset: string
original_filename: string
start_time: float
end_time: float
duration: float
-- schema metadata --
huggingface: '{"info": {"features": {"audio": {"bytes": {"dtype": "binary' + 549
to
{'audio': Audio(sampling_rate=None, decode=True, stream_index=None), 'text': Value('string'), 'speaker_id': Value('string'), 'emotion': Value('string'), 'language': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2361, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1905, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
                  for key, pa_table in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 106, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 73, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              audio: struct<bytes: binary, path: string>
                child 0, bytes: binary
                child 1, path: string
              text: string
              speaker_id: string
              language: string
              emotion: string
              original_dataset: string
              original_filename: string
              start_time: float
              end_time: float
              duration: float
              -- schema metadata --
              huggingface: '{"info": {"features": {"audio": {"bytes": {"dtype": "binary' + 549
              to
              {'audio': Audio(sampling_rate=None, decode=True, stream_index=None), 'text': Value('string'), 'speaker_id': Value('string'), 'emotion': Value('string'), 'language': Value('string')}
              because column names don't match

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test3434234

This is a merged speech dataset containing 848 audio segments from 2 source datasets.

Dataset Information

Total Segments: 848
Speakers: 2
Languages: tr
Emotions: angry, happy, neutral
Original Datasets: 2

Dataset Structure

Each example contains:

audio: Audio file (WAV format, original sampling rate preserved)
text: Transcription of the audio
speaker_id: Unique speaker identifier (made unique across all merged datasets)
emotion: Detected emotion (neutral, happy, sad, etc.)
language: Language code (en, es, fr, etc.)

Usage

Loading the Dataset

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Codyfederer/test3434234")

# Access the training split
train_data = dataset["train"]

# Example: Get first sample
sample = train_data[0]
print(f"Text: {sample['text']}")
print(f"Speaker: {sample['speaker_id']}")
print(f"Language: {sample['language']}")
print(f"Emotion: {sample['emotion']}")

# Play audio (requires audio libraries)
# sample['audio']['array'] contains the audio data
# sample['audio']['sampling_rate'] contains the sampling rate

Alternative: Load from JSONL

from datasets import Dataset, Audio, Features, Value
import json

# Load the JSONL file
rows = []
with open("data.jsonl", "r", encoding="utf-8") as f:
    for line in f:
        rows.append(json.loads(line))

features = Features({
    "audio": Audio(sampling_rate=None),
    "text": Value("string"),
    "speaker_id": Value("string"),
    "emotion": Value("string"),
    "language": Value("string")
})

dataset = Dataset.from_list(rows, features=features)

Dataset Structure

The dataset includes:

data.jsonl - Main dataset file with all columns (JSON Lines)
*.wav - Audio files under audio_XXX/ subdirectories
load_dataset.txt - Python script for loading the dataset (rename to .py to use)

JSONL keys:

audio: Relative audio path (e.g., audio_000/segment_000000_speaker_0.wav)
text: Transcription of the audio
speaker_id: Unique speaker identifier
emotion: Detected emotion
language: Language code

Speaker ID Mapping

Speaker IDs have been made unique across all merged datasets to avoid conflicts. For example:

Original Dataset A: speaker_0, speaker_1
Original Dataset B: speaker_0, speaker_1
Merged Dataset: speaker_0, speaker_1, speaker_2, speaker_3

Original dataset information is preserved in the metadata for reference.

Data Quality

This dataset was created using the Vyvo Dataset Builder with:

Automatic transcription and diarization
Quality filtering for audio segments
Music and noise filtering
Emotion detection
Language identification

License

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Citation

@dataset{vyvo_merged_dataset,
  title={test3434234},
  author={Vyvo Dataset Builder},
  year={2025},
  url={https://huggingface.co/datasets/Codyfederer/test3434234}
}

This dataset was created using the Vyvo Dataset Builder tool.

Downloads last month: 28

Size of downloaded dataset files:

227 MB

Size of the auto-converted Parquet files:

227 MB

Number of rows:

848