Datasets:

outlawmold
/

sinhala-tts-dataset

Error code:   FeaturesError
Exception:    ParserError
Message:      Error tokenizing data. C error: Expected 1 fields in line 37, saw 5

Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 246, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 4195, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2533, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2711, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2249, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
                  for batch_idx, df in enumerate(csv_file_reader):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
                  return self.get_chunk()
                         ^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
                  return self.read(nrows=size)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1923, in read
                  ) = self._engine.read(  # type: ignore[attr-defined]
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
                  chunks = self._reader.read_low_memory(nrows)
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
                File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
                File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
              pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 37, saw 5

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Sinhala TTS Dataset

Clean, segmented single-speaker Sinhala speech from the "Unlimited History" YouTube series by @sunchare. Built for TTS fine-tuning (F5-TTS, VITS, etc.).

Dataset Versions

`cc_v1` — Full dataset (63 videos)

Metric	Value
Utterances	22,441
Train / Val	21,319 / 1,122
Hours	23.23h
Mean duration	3.73s
Duration range	3.0s – 19.74s
Sample rate	22,050 Hz
Videos processed	63
Avg keep rate	84.4%

`cc_v1_tenvideo_baseline` — 10-video baseline

Metric	Value
Utterances	3,772
Train / Val	3,584 / 188
Hours	3.91h
Mean duration	3.73s
Duration range	3.0s – 19.74s
Sample rate	22,050 Hz

Pipeline

YouTube auto-CC (Sinhala) → text alignment → audio segmentation
→ quality filtering (duration, repetition, char-rate) → 22050Hz mono WAV

Source: YouTube auto-generated closed captions for Sinhala content. Each video is processed independently, then merged into the combined datasets.

Format

LJSpeech-style:

wavs/*.wav — 22050 Hz, 16-bit, mono
metadata.csv — filename|text|normalized_text (pipe-delimited, no header)

Audio files are organized in numbered subdirectories (wavs/00/, wavs/01/, etc.) for the full cc_v1 set, and flat wavs/ for the 10-video baseline.

Per-Video Raw Data

Each of the 10 baseline videos also has its raw (unsegmented) processing output under videos/<video_id>/, including:

Original long-form utterances before CC segmentation
manifest_kept.json / rejected_utterances.json — full filtering logs
run_info.json — processing metadata

Usage

import pandas as pd

# Load 10-video baseline
df = pd.read_csv(
    "hf://datasets/outlawmold/sinhala-tts-dataset/cc_v1_tenvideo_baseline/metadata_train.csv",
    sep="|", header=None, names=["id", "text", "normalized"]
)
print(f"Training utterances: {len(df)}")

Roadmap

10-video CC baseline (3.91h)
Full 63-video CC pipeline (23.23h)
Next 10 videos batch processing
TTS model fine-tuning (F5-TTS)

License

CC-BY-4.0. Source audio from YouTube; transcripts are auto-generated captions.

Downloads last month: 5,955

Total file size:

5.63 GB