|
|
--- |
|
|
title: Audio Reasoning & Step-Audio-R1 Explorer |
|
|
emoji: ๐ง |
|
|
colorFrom: purple |
|
|
colorTo: blue |
|
|
sdk: gradio |
|
|
sdk_version: 4.44.0 |
|
|
app_file: app.py |
|
|
pinned: false |
|
|
license: cc-by-4.0 |
|
|
short_description: Interactive guide to audio reasoning and Step-Audio-R1 model |
|
|
tags: |
|
|
- audio |
|
|
- reasoning |
|
|
- multimodal |
|
|
- step-audio-r1 |
|
|
- LALM |
|
|
- chain-of-thought |
|
|
- education |
|
|
--- |
|
|
|
|
|
# ๐ง Audio Reasoning & Step-Audio-R1 Explorer |
|
|
|
|
|
An interactive educational space exploring the groundbreaking concepts behind **audio reasoning** and the **Step-Audio-R1** model. |
|
|
|
|
|
--- |
|
|
|
|
|
## ๐ฏ What is Audio Reasoning? |
|
|
|
|
|
Audio reasoning is an AI model's ability to perform **deliberate, multi-step thinking processes** over audio inputs. This goes far beyond simple speech recognition (ASR) or audio classification. |
|
|
|
|
|
**Step-Audio-R1** is the first model to successfully unlock reasoning capabilities in the audio domain, solving the "inverted scaling anomaly" that plagued previous audio language models. |
|
|
|
|
|
--- |
|
|
|
|
|
## ๐ Features of This Space |
|
|
|
|
|
| Tab | Content | |
|
|
| :--- | :--- | |
|
|
| **๐ Introduction** | Overview of audio reasoning and key achievements. | |
|
|
| **๐ง Reasoning Types** | Interactive explorer for 5 types of audio reasoning. | |
|
|
| **๐ซ The Problem** | Understanding the inverted scaling anomaly. | |
|
|
| **๐ฌ MGRD Solution** | How Modality-Grounded Reasoning Distillation works. | |
|
|
| **๐๏ธ Architecture** | Step-Audio-R1 model architecture breakdown. | |
|
|
| **๐ Benchmarks** | Performance comparisons and results. | |
|
|
| **๐ฎ Interactive Demo** | Simulated audio reasoning examples. | |
|
|
| **๐ Applications** | Real-world use cases. | |
|
|
| **๐ Resources** | Papers, code, and references. | |
|
|
|
|
|
--- |
|
|
|
|
|
## ๐ฌ Key Innovation: MGRD |
|
|
|
|
|
**Modality-Grounded Reasoning Distillation (MGRD)** is the core innovation that makes Step-Audio-R1 work. It transforms the training process: |
|
|
|
|
|
> **Text-based reasoning** โ **Filter textual surrogates** โ **Keep acoustic-grounded chains** โ **Native Audio Think** |
|
|
|
|
|
This iterative process teaches the model to reason over **actual acoustic features** instead of text transcripts. |
|
|
|
|
|
--- |
|
|
|
|
|
## ๐ Performance |
|
|
|
|
|
Step-Audio-R1 achieves remarkable results in the audio domain: |
|
|
|
|
|
* โ
**Surpasses Gemini 2.5 Pro** on comprehensive audio benchmarks. |
|
|
* โ
**Comparable to Gemini 3 Pro** (state-of-the-art). |
|
|
* โ
**First successful test-time compute scaling** for audio. |
|
|
|
|
|
--- |
|
|
|
|
|
## ๐ Resources |
|
|
|
|
|
* ๐ **Step-Audio-R1 Paper** |
|
|
* ๐ป **GitHub Repository** |
|
|
* ๐ค **HuggingFace Collection** |
|
|
* ๐ฏ **Official Demo** |
|
|
|
|
|
--- |
|
|
|
|
|
## ๐ค Author |
|
|
|
|
|
**Mehmet Tuฤrul Kaya** |
|
|
|
|
|
* ๐ **GitHub:** [@mtkaya](https://github.com/mtkaya) |
|
|
* ๐ค **HuggingFace:** [tugrulkaya](https://huggingface.co/tugrulkaya) |
|
|
|
|
|
### ๐ Citation |
|
|
|
|
|
If you find this work useful, please cite the original paper: |
|
|
|
|
|
```bibtex |
|
|
@article{stepaudioR1, |
|
|
title={Step-Audio-R1 Technical Report}, |
|
|
author={Tian, Fei and others}, |
|
|
journal={arXiv preprint arXiv:2511.15848}, |
|
|
year={2025} |
|
|
} |