README.md

metadata

title: Audio Reasoning & Step-Audio-R1 Explorer
emoji: 🎧
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

🎧 Audio Reasoning & Step-Audio-R1 Explorer

An interactive educational space exploring the groundbreaking concepts behind audio reasoning and the Step-Audio-R1 model.

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🎯 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.

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🚀 Features of This Space

Tab	Content
🏠 Introduction	Overview of audio reasoning and key achievements.
🧠 Reasoning Types	Interactive explorer for 5 types of audio reasoning.
🚫 The Problem	Understanding the inverted scaling anomaly.
🔬 MGRD Solution	How Modality-Grounded Reasoning Distillation works.
🏗️ Architecture	Step-Audio-R1 model architecture breakdown.
📊 Benchmarks	Performance comparisons and results.
🎮 Interactive Demo	Simulated audio reasoning examples.
🚀 Applications	Real-world use cases.
📚 Resources	Papers, code, and references.

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🔬 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 → Filter textual surrogates → Keep acoustic-grounded chains → Native Audio Think

This iterative process teaches the model to reason over actual acoustic features instead of text transcripts.

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📊 Performance

Step-Audio-R1 achieves remarkable results in the audio domain:

• ✅ Surpasses Gemini 2.5 Pro on comprehensive audio benchmarks.
• ✅ Comparable to Gemini 3 Pro (state-of-the-art).
• ✅ First successful test-time compute scaling for audio.

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📚 Resources

• 📄 Step-Audio-R1 Paper
• 💻 GitHub Repository
• 🤗 HuggingFace Collection
• 🎯 Official Demo

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👤 Author

Mehmet Tuğrul Kaya

• 🐙 GitHub: @mtkaya
• 🤗 HuggingFace: tugrulkaya

📝 Citation

If you find this work useful, please cite the original paper:

@article{stepaudioR1,
  title={Step-Audio-R1 Technical Report},
  author={Tian, Fei and others},
  journal={arXiv preprint arXiv:2511.15848},
  year={2025}
}