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Datasets:
yongyizang
/
MSRBench

Tasks:
Audio-to-Audio
Modalities:
Audio
License:
Dataset card Data Studio Files
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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ValueError
Message:      Invalid string class label MSRBench@1b7087548d99cda8cec39be8525532bf67cce2af
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1537, in _prepare_split_single
                  example = self.info.features.encode_example(record) if self.info.features is not None else record
                            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
                  return encode_nested_example(self, example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ~~~~~~~~~~~~~~~~~~~~~^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
                  example_data = self.str2int(example_data)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
                  output = [self._strval2int(value) for value in values]
                            ~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label MSRBench@1b7087548d99cda8cec39be8525532bf67cce2af
              
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1382, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1560, 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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MSRBench: A Benchmarking Dataset for Music Source Restoration

MSRBench is the validation dataset for the MSR Challenge 2025 (https://msrchallenge.com); it contains 250 professionally mixed audio clips and their corresponding ground-truth targets under both original mix and 12 degradation scenarios in three categories.

Download

hf download yongyizang/MSRBench --repo-type dataset --local-dir {your output dir}

Total file size after unzipping is 28.7 GB.

Folder Structure 

{root-of-this-repo}/
└── {Stem_Name}.zip
(after unzipping...)
    β”œβ”€β”€ mixture/
    β”‚   β”œβ”€β”€ {song_id}_DT{degradation_type_id}.flac
    β”‚   β”œβ”€β”€ {song_id}_DT{degradation_type_id}.flac
    β”‚   └── ...
    └── targets/
        β”œβ”€β”€ {song_id}.flac
        β”œβ”€β”€ {song_id}.flac
        └── ...

Every *.flac file is 48 kHz stereo; each {stem_name} contains 250 song_ids, corresponding to 250 song clips; each song_id has 13 degradation types.

Available Stems

  • Vocals
  • Guitars
  • Bass
  • Keyboards
  • Synthesizers
  • Drums
  • Percussions
  • Orchestral Elements

Degradation Types

DT0: Original mixture produced by mixing engineers.

DT1-4: Analog and Environmental Distortions

Radio (DT1)

Simulates FM broadcasting using GNU Radio's stereo multiplex encoding/decoding blocks with standard broadcast parameters:

Signal Processing Parameters:

  • Audio sampling rate: 44.1 kHz
  • Quadrature rate: 220.5 kHz
  • Pre-emphasis/de-emphasis time constant: 75 ΞΌs (US standard)
  • Maximum frequency deviation: 75 kHz
  • Stereo pilot tone: 19 kHz

Channel Model:

  • Rayleigh fading: 8-sinusoid sum-of-sinusoids model with 20 Hz maximum Doppler shift
  • Carrier frequency offset: Οƒ = 0.1, max 1 kHz variations
  • Multipath channel: 3-tap configuration
    • Delays: [0, 0.1, 0.5] ms
    • Relative magnitudes: [1.0, 0.8, 0.3]
  • Noise: Additive white Gaussian noise at approximately 26 dB SNR (noise amplitude = 0.05)

Cassette (DT2)

Models magnetic tape coloration and noise using the DAW Cassette plugin by Klevgrand.[^1]

Vinyl (DT3)

Reproduces playback artifacts including crackle and mechanical noise using iZotope Vinyl,[^2] configured with the "1970" preset.

Live Sound (DT4)

Generated using:

  • Impulse responses from PyRoomAcoustics
  • Bandpass filtering to approximate phone microphone characteristics
  • Environmental noise from the WHAM! dataset 48 kHz version mixed at approximately 20 dB SNR

DT5-8: Traditional Lossy Audio Codecs

DT5: 64 Kbps AAC

DT6: 64 Kbps MP3

DT7: 128 Kbps AAC

DT8: 128 Kbps MP3

DT9-12: Neural Audio Codecs

DT9: 22 kHz Descript Audio Codec (DAC)

DT10: 44 kHz DAC

DT11: 6 Kbps Encodec

DT12: 3 Kbps Encodec

[^1]: Klevgrand DAW Cassette [^2]: iZotope Vinyl
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Total file size:
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