---
title: A2R-30B-A3B Speaker-Attributed Reasoning
emoji: 🗣️
colorFrom: purple
colorTo: green
sdk: gradio
sdk_version: 6.26.0
app_file: app.py
python_version: "3.12"
short_description: Ask who said what in a multi-speaker recording
startup_duration_timeout: 1h
---

# A2R-30B-A3B — who said what?

Demo of [`PleasedPenguin/A2R-30B-A3B`](https://huggingface.co/PleasedPenguin/A2R-30B-A3B),
the model from **"HEAR Who Said What: Unlocking Speaker-Attributed Reasoning via
Counterfactual Voice Grounding"** ([paper](https://huggingface.co/papers/2608.29120),
[code](https://github.com/dwsmart32/HEAR),
[project page](https://attributetoreason.github.io/AttributeToReason/)).

A2R is `Qwen/Qwen3-Omni-30B-A3B-Instruct` post-trained with GRPO on counterfactual
audio containing speaker-level hard negatives, so it grounds answers in *vocal
identity* rather than in the transcript.

Prompt formatting, system prompt and sampling defaults (`temperature=0.6`,
`top_p=0.95`) follow the authors' evaluation harness.

## Example audio attribution

The bundled example clips are excerpts of the
[AMI Meeting Corpus](https://huggingface.co/datasets/diarizers-community/ami),
licensed **CC BY 4.0** — one of the source corpora behind the HEAR benchmark.
The HEAR benchmark audio itself is not redistributable and is therefore not
bundled here.