The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 198, in _split_generators
for pa_metadata_table in self._read_metadata(downloaded_metadata_file, metadata_ext=metadata_ext):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 309, in _read_metadata
for df in 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 4 fields in line 32, saw 5
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/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Description
This dataset contains 50 clean audio recordings for Text-to-Speech training, recorded by a single speaker. Created for LIN3046 Computational Linguistics Assignment 2.
- Total Duration: Approximately 300 seconds (over 3 minutes)
- Number of Samples: 50
- Language: Mandarin Chinese (40 sentences) + English (10 sentences)
- Speaker: stuedent1
- Recording Environment: Quiet room using iPad Voice Memo
- Audio Format: WAV (16-bit PCM, 44100Hz)
- Dataset Size: Approximately 50MB
Collection and Processing Steps
1. Script Preparation
- Prepared 50 sentences covering daily conversation, academic topics, and technology
- Included 10 English sentences for multilingual coverage
- Organized sentences in metadata.csv with exact transcriptions
2. Recording Process
- Recorded using iPad's Voice Memo application
- Divided recording into 5 segments for better quality control
- Ensured consistent volume and microphone distance
- Recorded in a quiet environment to minimize background noise
3. Audio Processing
- Converted recordings from MP4 to WAV format using online converter
- Split long recordings into individual sentence-level clips
- Trimmed leading and trailing silence to less than 0.5 seconds
- Named files sequentially (s001.wav to s050.wav)
- Organized files in
wavs/directory
4. Quality Assurance
- Verified text-audio alignment for all 50 samples
- Checked audio clarity and absence of excessive noise
- Confirmed total duration exceeds the 3-minute requirement
- Ensured metadata.csv correctly references all audio files
Technical and Linguistic Issues Encountered
Issue 1: Format Conversion on Mobile Device
Problem: Initial recordings were saved in MP4 format by the Voice Memo app, but the assignment requires WAV format for TTS compatibility. Finding a reliable conversion tool for iPad was challenging.
Solution: Used online-audio-converter.com through Safari browser. The website allowed batch conversion with correct specifications (16-bit, 44100Hz). After conversion, verified file integrity by checking sample rate and ensuring all files were playable.
Issue 2: Maintaining Consistency Across Recording Sessions
Problem: Recording in 5 separate segments led to slight variations in audio quality, including different background noise levels and minor volume differences between segments.
Solution: Applied basic noise reduction using audio editing tools and normalized volume levels across all files. More importantly, maintained the same recording position and environment for all sessions to minimize variations.
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