Datasets:

Tnaot
/

large-dataset-audio

Error code:   DatasetGenerationError
Exception:    HfHubHTTPError
Message:      429 Client Error: Too Many Requests for url: https://huggingface.co/datasets/Tnaot/large-dataset-audio/resolve/7e5eb9de649f4a96cb2537cc82fb16f325f65465/audio/audio_00469.mp3 (Request ID: Root=1-693aa9a6-6a1924020f1fd1e1784ad4bc;1032a286-70ba-4501-8d91-49daa7000c89)

maximum queue size reached
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 409, in hf_raise_for_status
                  response.raise_for_status()
                File "/usr/local/lib/python3.12/site-packages/requests/models.py", line 1026, in raise_for_status
                  raise HTTPError(http_error_msg, response=self)
              requests.exceptions.HTTPError: 429 Client Error: Too Many Requests for url: https://huggingface.co/datasets/Tnaot/large-dataset-audio/resolve/7e5eb9de649f4a96cb2537cc82fb16f325f65465/audio/audio_00469.mp3
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1586, in _prepare_split_single
                  writer.write(example, key)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 623, in write
                  self.write_examples_on_file()
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 581, in write_examples_on_file
                  self.write_batch(batch_examples=batch_examples)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 701, in write_batch
                  self.write_table(pa_table, writer_batch_size)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 716, in write_table
                  pa_table = embed_table_storage(pa_table)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in embed_table_storage
                  embed_array_storage(table[name], feature, token_per_repo_id=token_per_repo_id)
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2124, in embed_array_storage
                  return feature.embed_storage(array, token_per_repo_id=token_per_repo_id)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/audio.py", line 291, in embed_storage
                  (path_to_bytes(x["path"]) if x["bytes"] is None else x["bytes"]) if x is not None else None
                   ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/py_utils.py", line 310, in wrapper
                  return func(value) if value is not None else None
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/audio.py", line 287, in path_to_bytes
                  return f.read()
                         ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 813, in read_with_retries
                  out = read(*args, **kwargs)
                        ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 728, in track_read
                  out = f_read(*args, **kwargs)
                        ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 1012, in read
                  out = f.read()
                        ^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 728, in track_read
                  out = f_read(*args, **kwargs)
                        ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 1078, in read
                  hf_raise_for_status(self.response)
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 482, in hf_raise_for_status
                  raise _format(HfHubHTTPError, str(e), response) from e
              huggingface_hub.errors.HfHubHTTPError: 429 Client Error: Too Many Requests for url: https://huggingface.co/datasets/Tnaot/large-dataset-audio/resolve/7e5eb9de649f4a96cb2537cc82fb16f325f65465/audio/audio_00469.mp3 (Request ID: Root=1-693aa9a6-6a1924020f1fd1e1784ad4bc;1032a286-70ba-4501-8d91-49daa7000c89)
              
              maximum queue size reached
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1334, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 911, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1447, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1604, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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audio audio

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khmer_speech_dataset

Khmer speech dataset with transcriptions, speaker labels, and metadata.

Dataset Description

This dataset contains Khmer (Cambodian) speech recordings with detailed transcriptions and annotations.

Dataset Statistics

Metric	Value
Total Examples	9,285
Total Duration	336.68 hours
Average Duration	130.54 seconds
Total Words	1,336,611
Khmer Words	994,050 (74.4%)
English Words	340,127 (25.4%)
Unique Sources	2857
Unique Tags	2092

Source Distribution

Source Type	Count
youtube	5,947
unknown	16
conversation	696
telegram	2,626

Speaker Distribution

Speakers	Count	Duration (hours)
0	2	0.00 (0.0%)
1	3,060	33.97 (10.1%)
2	2,855	137.80 (40.9%)
3	2,892	141.56 (42.0%)
4	387	18.99 (5.6%)
5	65	3.18 (0.9%)
6	16	0.78 (0.2%)
7	2	0.10 (0.0%)
8	5	0.25 (0.1%)
12	1	0.05 (0.0%)

Top Tags

Tag	Count
overlapping	5,982
laughing	4,736
drag_tone	3,705
fast	3,337
mocking	1,821
high_pitch	1,792
shout	1,597
frustrated	1,163
smack_lips	1,161
heavy_breathing	961
whisper	886
softly	856
stutter	726
serious	664
normal	638
sigh	465
hesitant	433
normal_tone	428
panic	423
thinking	399

Dataset Structure

Data Fields

audio: Audio file path/bytes
text_raw: Raw transcription with speaker labels and tags
text_clean: Cleaned transcription (no tags, no speaker labels)
duration_seconds: Audio duration in seconds
speaker_count: Number of speakers in the audio
speakers: List of speaker IDs
tags: List of normalized annotation tags
english_words: Count of English words
khmer_words: Count of Khmer words
total_words: Total word count
chunk_id: Chunk index within original audio
original_name: Name of original audio file
source_type: Source type (telegram, youtube, conversation, unknown)
source_folder: Original folder name
telegram_chat_id: Telegram chat ID (if applicable)

Tag Categories

Speech markers: hesitant, thinking, confused, drag_tone, overlapping
Audio markers: music, low_quality, noise
Language markers: english, khmer

Usage

from datasets import load_dataset

# Load dataset
dataset = load_dataset("path/to/dataset")

# Access examples
for example in dataset["train"]:
    audio = example["audio"]
    text = example["text_clean"]
    print(f"Duration: {example['duration_seconds']:.2f}s")
    print(f"Text: {text[:100]}...")

License

This dataset is released under CC-BY-NC-4.0 license.

Citation

If you use this dataset, please cite:

@dataset{khmer_speech_dataset,
  title={Khmer Speech Dataset},
  year={2024},
  url={https://huggingface.co/datasets/...}
}

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