Datasets:
You need to agree to share your contact information to access this dataset
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
This is the held-out evaluation set for the Audio2Tool Leaderboard. By requesting access you agree to use it only for evaluating models and submitting to the leaderboard, not to redistribute the audio, and not to attempt to reconstruct or publish the hidden ground-truth labels.
Log in or Sign Up to review the conditions and access this dataset content.
Audio2Tool Private Eval Set
Held-out evaluation set for the Audio2Tool Leaderboard. It is a random subset of the private split of the Audio2Tool dataset: up to 200 queries per tier across all 8 tiers (1,579 samples). Ground-truth labels are not published — submissions are scored on the leaderboard Space against hidden labels.
Contents
metadata.jsonl— one row per sample:sample_id,tier,audio(list of wav paths, ordered turns fortier7_multiturn)audio/<tier>/query_XXXXX/*.wav— audio files
Tools available to the model are described in
tools_registry.csv
of the main dataset.
How to submit
- For each row in
metadata.jsonl, run your model on the audio and produce a tool-call prediction string, e.g.setZoneTemperature(zone=Driver, temperature=21.0). For multi-intent samples, output multiple calls in one string, first call is the primary tool:setLockState(state=Locked) setFanSpeed(level=7) - Write predictions as JSONL, one row per sample:
{"sample_id": "tier1_direct/00042", "prediction": "setZoneTemperature(zone=Driver, temperature=21.0)"}
- Upload the file on the Submit tab of the leaderboard Space.
Evaluation
For each sample the leaderboard computes (same normalization as the benchmark code):
- Tool Accuracy — predicted primary tool name matches ground truth (case-insensitive)
- Exact Match — tool and all parameters match exactly
- Param F1 — F1 over predicted vs ground-truth parameter key/value pairs (0 when the tool is wrong)
Scores are reported per tier plus a macro-average across tiers.
Running with the benchmark code
The Audio2Tool benchmark repo
can produce predictions for the supported models; the eval set follows the
same layout as the public release, so the release dataset loader reads
metadata.jsonl directly.
- Downloads last month
- 29