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1
Parallel processing in speech perception with local and global representations of linguistic context
In: eLife (2022)
Abstract: Speech processing is highly incremental. It is widely accepted that human listeners continuously use the linguistic context to anticipate upcoming concepts, words, and phonemes. However, previous evidence supports two seemingly contradictory models of how a predictive context is integrated with the bottom-up sensory input: Classic psycholinguistic paradigms suggest a two-stage process, in which acoustic input initially leads to local, context-independent representations, which are then quickly integrated with contextual constraints. This contrasts with the view that the brain constructs a single coherent, unified interpretation of the input, which fully integrates available information across representational hierarchies, and thus uses contextual constraints to modulate even the earliest sensory representations. To distinguish these hypotheses, we tested magnetoencephalography responses to continuous narrative speech for signatures of local and unified predictive models. Results provide evidence that listeners employ both types of models in parallel. Two local context models uniquely predict some part of early neural responses, one based on sublexical phoneme sequences, and one based on the phonemes in the current word alone; at the same time, even early responses to phonemes also reflect a unified model that incorporates sentence-level constraints to predict upcoming phonemes. Neural source localization places the anatomical origins of the different predictive models in nonidentical parts of the superior temporal lobes bilaterally, with the right hemisphere showing a relative preference for more local models. These results suggest that speech processing recruits both local and unified predictive models in parallel, reconciling previous disparate findings. Parallel models might make the perceptual system more robust, facilitate processing of unexpected inputs, and serve a function in language acquisition.
Keyword: Neuroscience
URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8830882/
https://doi.org/10.7554/eLife.72056
http://www.ncbi.nlm.nih.gov/pubmed/35060904
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2
Using surprisal and fMRI to map the neural bases of broad and local contextual prediction during natural language comprehension ...
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3
Community-level Research on Suicidality Prediction in a Secure Environment: Overview of the CLPsych 2021 Shared Task
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4
Connecting Documents, Words, and Languages Using Topic Models
Yang, Weiwei. - 2019
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5
Assessing Composition in Sentence Vector Representations ...
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6
Relating lexical and syntactic processes in language: Bridging research in humans and machines
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7
Guided Probabilistic Topic Models for Agenda-setting and Framing
Nguyen, Viet An. - 2015
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8
Soft syntactic constraints for Arabic-English hierarchical phrase-based translation
In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 26 (2012) 1-2, 137-157
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OLC Linguistik
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9
Crowdsourced Monolingual Translation
Hu, Chang. - 2012
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10
Decision Tree-based Syntactic Language Modeling
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11
Modeling Dependencies in Natural Languages with Latent Variables
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12
Exploiting syntactic relationships in a phrase-based decoder: an exploration
In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 24 (2010) 2, 123-140
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OLC Linguistik
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13
Gibbs Sampling for the Uninitiated
In: DTIC (2010)
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14
Structured local exponential models for machine translation
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15
A Formal Model of Ambiguity and its Applications in Machine Translation
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16
Extending Phrase-Based Decoding with a Dependency-Based Reordering Model
In: DTIC (2009)
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17
Extending Phrase-Based Decoding with a Dependency-Based Reordering Model
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18
COMPUTATIONAL ANALYSIS OF THE CONVERSATIONAL DYNAMICS OF THE UNITED STATES SUPREME COURT
Hawes, Timothy. - 2009
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19
Fine-Grained Linguistic Soft Constraints on Statistical Natural Language Processing Models
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20
Generalizing Word Lattice Translation
In: DTIC (2008)
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