Vaissiere, J. (1981). Speech recognition programs as models of speech perception. In T. Myers, J. Laver, & J. Anderson (Eds.), The cognitive representation of speech (pp. 443-457). Amsterdam, New York, Oxford:
Dissecting neural computations in the human auditory pathway using deep neural networks for speech Article Open access 30 October 2023 Deep neural network models reveal interplay of peripheral coding and stimulus statistics in pitch perception Article Open access 14 December 2021 Models optimized for...
Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models arXiv 2025-05-08 Github - VITA-Audio: Fast Interleaved Cross-Modal Token Generation for Efficient Large Speech-Language Model arXiv 2025-05-06 Github Local Demo Skywork R1V2: Multimodal Hybrid Reinforcement Le...
Although many researchers have examined the role that binaural cues play in the perception of spatially separated speech signals, relatively little is know... DS Brungart - 《Journal of the Acoustical Society of America》 被引量: 1096发表: 2001年 Theory of binaural interaction based on auditory‐...
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Note that although syntactic rule violations and semantic mismatches also fit the above definition, they will not be discussed here as these deviations are not of auditory nature and they are processed at higher levels of the hierarchy; for models of speech perception explaining syntactic and semanti...
Speech-perceptionCell AssembliesNeighborhood ActivationLanguage RehabilitationBackground: The results from previous studies have indicated that a pre-attentive component of the event-related potential (ERP), the mismatch negativity (MMN), may be an objective measure of the automatic auditory processing of ...
MagnifierBench OtterHD: A High-Resolution Multi-modality Model Link A benchmark designed to probe models' ability of fine-grained perception HallusionBench HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LL...
There are also reasons to assume that listening to speech in unfavourable condi- tions, such as synthetic speech, is preferred at a slower tempo than the conversational rate in natural speech, which affects timing properties of synthetic speech. Therefore, in our view perception data of several ...
In conclusion, combining large language models with multi-modal learning represents a remarkable milestone in AI’s evolution. It is a testament to the field’s relentless pursuit of understanding and emulating the depth and richness of human sensory perception. As AI continues its journey into this...