A Generalized Formalism of Auto-Regressive Decoding for Speech Processing
In speech processing, most state-of-the-art sequence prediction models rely on auto-regressive (AR) strategies to generate output sequences based on the raw predictions of the model. Despite their crucial role in the inference process, a comprehensive overview of AR strategies as a unified field is lacking, due largely to implicit and multiple definitions of next-token decoding. This context complicates the choice, comparison, and evaluation of strategies, while creating inconsistencies in the characterization of approaches as auto-regressive or not. We begin by setting explicit inclusion criteria for the field of AR search in speech processing, and derive a generalized theoretical framew...
| Authors | Julia Gachot, Philipp Allgeuer, Marie S. Bauer et al. |
|---|---|
| Primary category | cs.SD |
| Published | 16 June 2026 |
| Last updated at source | 16 June 2026 |
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