Datasets:

amaai-lab
/

MusicListenBench

license: apache-2.0
configs:
  - config_name: clean
    default: true
    data_files:
      - split: train
        path: data/train/**
      - split: test
        path: data/test/**
  - config_name: flip_stay
    data_files:
      - split: test
        path: data/test_flip_stay/**

MusicListenBench

Audio and item files for MusicListenBench: Can Audio LLMs Hear the Difference Yet?

Each test item is one audio file (clip A, one second of silence, clip B) and one question about the pair: same melody, same chord, same instrument, or which clip is faster. Every item has two variants. In the FLIP variant the music changes, so the correct answer changes. In the STAY variant only the sound changes (room echo, EQ, background hiss, transposition), so the correct answer stays. A model that ignores the audio scores 50% on average, whatever letter it prefers.

Code, scoring and the generator: https://github.com/AMAAI-Lab/MusicListenBench/tree/release Leaderboard: https://amaai-lab.github.io/MusicListenBench/

Splits

Config	Split	Files	Folder
`clean`	`train`	10,000 (2,500 per task)	`data/train/`
`clean`	`test`	1,000 (250 per task)	`data/test/`
`flip_stay`	`test`	2,000 (500 per task: 250 FLIP and 250 STAY)	`data/test_flip_stay/`

Each folder holds the audio in one sub-folder per task (Q1_melody, Q2_harmony, Q3_timbre, Q4_rhythm) and a metadata.jsonl. Audio is 16-bit PCM WAV, 44.1 kHz, mono. A file is clip A, one second of silence and clip B, so it is 6.0 s long for melody and timbre, 5.0 s for harmony and 9.0 s for rhythm.

from datasets import load_dataset
train = load_dataset("amaai-lab/MusicListenBench", "clean", split="train")
test = load_dataset("amaai-lab/MusicListenBench", "clean", split="test")
flip_stay = load_dataset("amaai-lab/MusicListenBench", "flip_stay", split="test")

Columns

audio: the file
item_id: the file name without .wav
task: Q1_melody, Q2_harmony, Q3_timbre or Q4_rhythm
question: the question that is asked with the audio
answer: the correct answer, A or B
condition, factor (flip_stay only): flip or stay, and what was changed. FLIP edits are note_identity, third_quality, instrument and pulse_rate; STAY effects are eq, hiss, room and transposition.

Every question ends with an instruction that says which letter means which answer; the meaning differs between question wordings.

Item files

data/train.json, data/eval.json (the clean test items), data/eval_perturb.json (the FLIP/STAY test items) and data/eval_perturb.meta.jsonl are the item files of the code repository. They list the same items as the metadata, with the question ending in the <audio> placeholder. The audio paths in them are relative to data/train/, data/test/ and data/test_flip_stay/.

Licences

The audio is rendered with the soundfonts FluidR3 GM, GeneralUser GS and MuseScore General; follow the licence terms that come with them. The benchmark audio contains no recordings of people and no copyrighted musical works.