metadata

license: cc-by-4.0
dataset_info:
  features:
    - name: question-type
      dtype: string
    - name: description
      dtype: string
    - name: model-1
      dtype: string
    - name: track-1-id
      dtype: int64
    - name: track-1-begin
      dtype: string
    - name: track-1-end
      dtype: string
    - name: model-2
      dtype: string
    - name: track-2-id
      dtype: int64
    - name: track-2-begin
      dtype: string
    - name: track-2-end
      dtype: string
    - name: answer
      dtype: int64
  splits:
    - name: train
      num_bytes: 2396604
      num_examples: 15600
  download_size: 295100
  dataset_size: 2396604
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - music
size_categories:
  - 10K<n<100K

from datasets import load_dataset
dataset = load_dataset('disco-eth/AIME-survey')

AIME Survey: AI Music Evaluation Dataset

This survey dataset accompanies the AIME audio dataset.

The AIME Survey dataset consists of 15,600 pairwise audio comparisons rated by more than 2,500 human participants regarding the music quality and text-audio alignment of 12 state-of-the-art music generation models (as of July 2024). The comparisons were made between 10 second snippets of the audio tracks.

The dataset contains the following fields:

question-type: The type of question for the evaluation of the two audio tracks. This can be either 'Text-Audio Alignment' or 'Music Quality'
description: The tag-based music description that was used to generate the tracks.
model-1: The music generation model that generated track-1.
track-1-id: The id for track-1. This corresponds to the id's in the AIME audio dataset.
track-1-begin: The timestamp for the begin of the audio snippet from track-1.
track-1-end: The timestamp for the end of the audio snippet from track-1.
model-2: The music generation model that generated track-2.
track-2-id: The id for track-2. This corresponds to the id's in the AIME audio dataset.
track-2-begin: The timestamp for the begin of the audio snippet from track-2.
track-2-end: The timestamp for the end of the audio snippet from track-2.
answer: Whether the participant preferred the audio snippet from track-1 (answer=1) or track-2 (answer=2).

For more information or to cite our work please see Benchmarking Music Generation Models and Metrics via Human Preference Studies.