Datasets:
Formats:
json
Size:
1K - 10K
Tags:
audio
text
audio-language-model
audio-text-alignment
instruction-following
rubric-based-evaluation
| # Human Preference | |
| This component contains 100 prompts derived from ASG-Bench, each used to | |
| independently generate three audio candidates with SeedAudio 1.0 | |
| (300 candidates in total), together with prompt-derived rubrics and | |
| annotations from seven human annotators. All released audio files are in | |
| WAV format. | |
| The release contains all 100 prompt groups and their individual annotation | |
| records. The paper evaluation uses 279 pairwise comparisons with a unique | |
| winning candidate and 84 three-candidate ranking groups with a unique | |
| modal ranking among valid complete annotations. | |
| ## Files | |
| ### `candidate_groups.jsonl` | |
| One unlabeled group per prompt. Each row contains `group_id`, `language`, | |
| `category`, `prompt`, and three nested candidates with `candidate_id`, `audio`, | |
| and `duration_seconds`. It intentionally contains no preference label so the | |
| groups can be independently re-annotated. | |
| ### `prompt_rubrics.jsonl` | |
| One prompt and its nested rubric list per row. Rubric fields are `rubric_id`, | |
| `question`, `axis`, `scope`, `subtype`, `domain`, `basis`, and `parent_ids`. | |
| The rubric questions are produced from each prompt using the structured | |
| rubric decomposition method proposed in FineAudio-Judge. | |
| ### `human_preference_annotations.jsonl` | |
| This file contains 700 individual annotation records, seven per prompt | |
| group. Annotators are identified by stable anonymous IDs | |
| `annotator_01` through `annotator_07`. | |
| Each row contains the annotation status, `unable_to_judge`, the | |
| best-to-worst candidate `ranking`, and the candidate `presentation_order`. | |
| ### `human_preference_pairwise.jsonl` | |
| This file contains 279 pairwise comparisons with a unique modal preference | |
| among the 300 possible candidate pairs across 100 prompt groups, based on | |
| the annotators' complete rankings. | |
| `label` identifies the winning candidate. `votes` records the vote counts | |
| for both candidates, together with unable-to-judge and missing or invalid | |
| annotations. `vote_pattern` records `winner_votes:loser_votes`. | |
| Consensus strata are: | |
| | Level | Definition | Observed vote patterns | Comparisons | | |
| |---|---|---|---:| | |
| | `high` | loser votes = 0 | `7:0`, `6:0`, `5:0`, `4:0` | 68 | | |
| | `medium` | loser votes = 1 | `6:1`, `5:1`, `4:1`, `3:1` | 91 | | |
| | `low` | loser votes >= 2 | `5:2`, `4:3`, `4:2`, `3:2` | 120 | | |
| Vote patterns are shown as `winner_votes:loser_votes`, with unable-to-judge | |
| and missing or invalid annotations counted separately. | |
| ### `human_preference_ranking.jsonl` | |
| This file contains the 84 three-candidate ranking groups used in the paper | |
| evaluation. Each reference ranking is the unique mode among the valid | |
| complete rankings submitted by the seven annotators. Groups with tied | |
| modal rankings are excluded. | |
| `label` gives the candidate order from best to worst. `vote_distribution` | |
| records each observed complete ranking and its count. `consensus_level` | |
| is `strict_majority` when the modal ranking receives at least four votes, | |
| and `unique_plurality` when the unique mode receives two or three votes. | |
| ## Categories | |
| | Category | Groups | | |
| |---|---:| | |
| | `Cinematic` | 18 | | |
| | `Environmental` | 20 | | |
| | `Field Reporting` | 19 | | |
| | `Narrational` | 19 | | |
| | `Podcast_Broadcast` | 24 | | |
| ## Evaluation protocol | |
| For each candidate audio, the judge jointly evaluates the rubrics derived | |
| from its prompt and predicts `yes` or `no` for each rubric. The proportion | |
| of `yes` predictions forms the candidate's prompt–audio consistency score: | |
| score = number of yes predictions / number of rubrics | |
| Candidates generated from the same prompt are compared and ranked by | |
| their consistency scores. Pairwise accuracy is evaluated against | |
| `human_preference_pairwise.jsonl`. A three-candidate ranking is counted | |
| as correct when the predicted order exactly matches the reference | |
| order in `human_preference_ranking.jsonl`. | |
| For pairwise evaluation, equal consistency scores for the two candidates | |
| count as an incorrect judgment. For three-candidate ranking evaluation, | |
| equal consistency scores for any two candidates count as an incorrect | |
| ranking. | |
| Evaluation is performed at the candidate-audio level, with multiple rubrics | |
| for the same candidate evaluated jointly in each model request. Longer | |
| rubric lists are divided into chunks of up to 80 questions by default. | |
| Predictions from all chunks are combined into a single consistency score | |
| for that candidate. | |