StepAudio 3 Gen Technical Report

Hugging Face Daily Papers Papers

Summary

StepAudio 3 Gen is a general-purpose audio generation model that unifies text-to-speech, voice design, sound effects, and music within a single discrete autoregressive framework using residual vector quantization tokens.

We introduce StepAudio 3 Gen, a general-purpose audio generation model that supports zero-shot text-to-speech (TTS), voice design, vocal generation, sound effects, music, vibe speech, and mixtures of multiple audio types within a unified framework. At its core, StepAudio 3 Gen is a discrete autoregressive generator that models audio directly over residual vector quantization (RVQ) tokens, departing from the diffusion Transformer-based continuous generation paradigm prevalent in recent general audio models. Its StepAudio Tokenizer represents general audio at 12.5 Hz in a shared 16 times 2048 residual code space, jointly quantizing semantic and waveform-level acoustic features so that each code layer preserves both types of information. For generation, the backbone predicts the first codebook along the time axis using autoregressive modeling, while a lightweight causal Transformer completes the remaining fifteen codebooks along the codebook axis. Our study further identifies three key design principles: (1) interference-aware progressive pretraining for acquiring audio capabilities while preserving the textual abilities of the large language model, (2) RVQ Adaptor for effectively incorporating multi-codebook acoustic representations, and (3) discrete autoregressive modeling over a shared representation across general audio domains. With progressive pretraining, multi-task instruction training, and supervised fine-tuning, StepAudio 3 Gen achieves state-of-the-art performance on both TTS and voice design, while retaining strong generation capabilities across speech, vocals, sound effects, and music. Audio samples are available at https://stepaudiollm.github.io/step-audio-3-gen/.
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Source: https://huggingface.co/papers/2609.12945 Published on Sep 11

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Abstract

StepAudio 3 Gen is a discrete autoregressive audio generation model using residual vector quantization tokens to unify text-to-speech, voice design, sound effects, and music within a single framework.

We introduce StepAudio 3 Gen, a general-purpose audio generation model that supports zero-shot text-to-speech (TTS), voice design, vocal generation, sound effects, music, vibe speech, and mixtures of multiple audio types within a unified framework. At its core, StepAudio 3 Gen is a discreteautoregressive generatorthat models audio directly overresidual vector quantization(RVQ) tokens, departing from the diffusion Transformer-based continuous generation paradigm prevalent in recent general audio models. ItsStepAudio Tokenizerrepresents general audio at 12.5 Hz in a shared 16 times 2048 residual code space, jointly quantizing semantic and waveform-level acoustic features so that each code layer preserves both types of information. For generation, the backbone predicts the first codebook along the time axis using autoregressive modeling, while a lightweightcausal Transformercompletes the remaining fifteen codebooks along the codebook axis. Our study further identifies three key design principles: (1)interference-aware progressive pretrainingfor acquiring audio capabilities while preserving the textual abilities of the large language model, (2)RVQ Adaptorfor effectively incorporatingmulti-codebook acoustic representations, and (3)discrete autoregressive modelingover a shared representation across general audio domains. With progressive pretraining, multi-task instruction training, and supervised fine-tuning, StepAudio 3 Gen achieves state-of-the-art performance on both TTS and voice design, while retaining strong generation capabilities across speech, vocals, sound effects, and music. Audio samples are available at https://stepaudiollm.github.io/step-audio-3-gen/.

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