Datasets:

Aananda-giri
/

openSLR-Nepali

Error code:   StreamingRowsError
Exception:    FileNotFoundError
Message:      datasets/Aananda-giri/openSLR-Nepali@eb4bcb62930df58bf5f0be281ab8d658ffd527e4/audio
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 "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2431, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1953, in __iter__
                  batch = formatter.format_batch(pa_table)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
                  batch = self.python_features_decoder.decode_batch(batch)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
                  return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2147, in decode_batch
                  decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1409, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/audio.py", line 203, in decode_example
                  f = xopen(path, "rb", download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 935, in xopen
                  file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/core.py", line 135, in open
                  return self.__enter__()
                         ^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__
                  f = self.fs.open(self.path, mode=mode)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open
                  f = self._open(
                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 275, in _open
                  return HfFileSystemFile(self, path, mode=mode, revision=revision, block_size=block_size, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 947, in __init__
                  self.details = fs.info(self.resolved_path.unresolve(), expand_info=False)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 711, in info
                  self.ls(parent_path, expand_info=False)
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 380, in ls
                  _raise_file_not_found(path, None)
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 1138, in _raise_file_not_found
                  raise FileNotFoundError(msg) from err
              FileNotFoundError: datasets/Aananda-giri/openSLR-Nepali@eb4bcb62930df58bf5f0be281ab8d658ffd527e4/audio

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OpenSLR Nepali Speech Dataset (Preprocessed)

Dataset Description

This is a preprocessed version of the Nepali speech dataset from OpenSLR, ready for training speech models including Automatic Speech Recognition (ASR) and Text-to-Speech (TTS).

Dataset Statistics

Total Audio Files: 118,231
Total Duration: 57.34 hours
Sample Rate: 16kHz
Channels: Mono
Format: WAV

Preprocessing Applied

Text Preprocessing:
- Text cleaning and normalization
- Number to text conversion
- Nepali character standardization
Audio Preprocessing:
- Resampled to 16kHz mono
- Quality filtering (duration: 0.5-20s, SNR > 10dB)
- Silence detection and handling
- RMS normalization
- Pre-emphasis filter (coefficient=0.97)
Quality Checks:
- Verified all audio files exist
- Removed empty transcripts
- Duration validation

Dataset Structure

.
├── metadata.csv          # Contains file_name, transcript, duration, sample_rate, gender, quality, snr_db
└── audio/               # Directory containing all audio files
    └── *.wav            # Audio files

metadata.csv Format

Column	Description
file_name	Relative path to audio file (audio/filename.wav)
transcript	Nepali text transcript
duration	Audio duration in seconds
sample_rate	Sample rate (16000 Hz)
gender	Speaker gender (male/female)
quality	Audio quality rating (high/low)
snr_db	Signal-to-noise ratio in decibels

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Aananda-giri/openSLR-Nepali")

# Access a sample
sample = dataset['train'][0]
print(f"Audio: {sample['audio']}")
print(f"Transcript: {sample['transcript']}")
print(f"Duration: {sample['duration']} seconds")

Use Cases

This dataset is suitable for:

Automatic Speech Recognition (ASR): Train models to transcribe Nepali speech to text
Text-to-Speech (TTS): Train models to synthesize Nepali speech from text
Speech Research: Study Nepali phonetics, prosody, and acoustic characteristics

Source

Original dataset from OpenSLR:

OpenSLR Nepali Speech Dataset

License

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

Citation

If you use this dataset, please cite the original OpenSLR dataset:

@misc{openslr_nepali,
  title={Nepali Speech Dataset},
  author={OpenSLR},
  howpublished={\url{https://www.openslr.org/}},
  year={2020}
}

Preprocessing Details

This dataset was preprocessed using a custom pipeline that includes:

Text normalization for Nepali language
Audio quality filtering and enhancement
Standardization to 16kHz mono format
Vocabulary and character mapping generation

Preprocessed on: 2025-11-17

Contact

For questions or issues with this preprocessed version, please open an issue in the dataset repository.

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