Paper page - StepAudio 2.5 Technical Report

Source: https://huggingface.co/papers/2605.23463 Published on May 22

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Submitted byhttps://huggingface.co/giantPanda0906

Yangon May 25

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Abstract

StepAudio 2.5 is a unified audio-language model that matches specialized systems in ASR, TTS, and real-time spoken interaction by using task-tailored reinforcement learning from human feedback to optimize shared representations across different operational modes.

Unified audio-language modelinghas emerged as a prominent trend in modern speech systems, promising to bring the reasoning capabilities of large language models to auditory tasks. However, existing unified foundations often struggle to match the depth of specialized systems acrossautomatic speech recognition(ASR),text-to-speech synthesis(TTS), and realtime spoken interaction. Bridging this gap remains an open challenge. This report presents StepAudio 2.5, a unified audio-language foundation model that matches or exceeds specialized systems across all three capabilities. Rather than treating these tasks as architecturally distinct, we operate on the premise that once text and audio share amultimodal representational space, task specialization becomes a matter of operational regimes: data construction, optimization targets, and decoding constraints. Guided by this insight, we advance thepost-training paradigmfrom standard supervised learning to task-tailoredReinforcement Learning from Human Feedback(RLHF), using it as the primary mechanism to define complex optimization targets. We leverage thisRLHF-centric alignment, alongside specialized decoding, to shape a shared backbone into three distinct operational modes. Concretely, the ASR branch advances transcription efficiency viaverifiable multi-token decoding; the TTS branch achieves controllable, expressive synthesis throughpreference-based RLHFand context-rich supervision; and the Realtime branch realizes low-latency, persona-consistent dialogue viagenerative reward modelingwithin anRLHFframework. On standard benchmarks, StepAudio 2.5 achieves state-of-the-art results across ASR, TTS, and Realtime, demonstrating that a singular audio-language foundation can successfully internalize the distinct deployment objectives of speech understanding, generation, and live interaction.

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