.png){kind=icon}
Return
Decoupling speech processing from time
.png){kind=icon}
OA
AI
DOI：10.1016/j.tics.2025.05.017.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Speech processing has long been defined by unifying principles that suggest that the dynamics of word recognition are closely coupled to the unfolding signal. These argue that candidates are activated immediately and updated incrementally as the signal unfolds, information decays to make room for more input, and internal representations are defined by temporal order. However, converging results from several domains suggest that these principles are less ubiquitous than has long been assumed. Perceptual information does not decay rapidly; buffers in the system may block incremental processing, words are not strictly ordered, and listeners in many real-world circumstances adopt a profile of word recognition that is not incremental. This has strong implications for current evaluation of computational models and requires new frameworks for understanding the basic systems that make up speech processing.
Keywords:
Speech processing
Word recognition
Incremental processing
Temporal order
Computational models
Journal
IF:
17.2
Papers:
3.6K
Citations:
3.5W
Organization
Cited Papers
.png){kind=icon}
ShareSaveChanging only the probability that spoken words will be distorted changes how they are recognized
OAAI
OAAIShareSaveShareSave
View more