scholarly journals A computational model of binaural speech recognition: Role of across-frequency vs. within-frequency processing and internal noise

2011 ◽  
Vol 53 (6) ◽  
pp. 924-940 ◽  
Author(s):  
Kalle J. Palomäki ◽  
Guy J. Brown
Keyword(s):  
Speech Recognition ◽  
Computational Model ◽  
Internal Noise ◽  
Frequency Processing

scholarly journals A computational model of cell culture dynamics: the role of connectivity and synaptic receptors in the appearance of synchronized bursting events

2015 ◽  
Vol 16 (S1) ◽  
Author(s):  
Davide Lonardoni ◽  
Stefano Di Marco ◽  
Hayder Amin ◽  
Luca Berdondini ◽  
Thierry Nieus
Keyword(s):  
Cell Culture ◽  
Computational Model ◽  
Synaptic Receptors ◽  
Bursting Events

Internal noise suppression for speech recognition by small robots

2005 ◽  
Author(s):  
Akinori Ito ◽  
Takashi Kanayama ◽  
Motoyuki Suzuki ◽  
Shozo Makino
Keyword(s):  
Speech Recognition ◽  
Noise Suppression ◽  
Internal Noise

scholarly journals Interacting roles of lateral and medial Orbitofrontal cortex in decision-making and learning : A system-level computational model

2019 ◽  
Author(s):  
Bhargav Teja Nallapu ◽  
Frédéric Alexandre
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Computational Model ◽  
Orbitofrontal Cortex ◽  
Temporal Dynamics ◽  
System Level ◽  
Interacting Networks ◽  
Cortical Regions ◽  
Experimental Findings

AbstractIn the context of flexible and adaptive animal behavior, the orbitofrontal cortex (OFC) is found to be one of the crucial regions in the prefrontal cortex (PFC) influencing the downstream processes of decision-making and learning in the sub-cortical regions. Although OFC has been implicated to be important in a variety of related behavioral processes, the exact mechanisms are unclear, through which the OFC encodes or processes information related to decision-making and learning. Here, we propose a systems-level view of the OFC, positioning it at the nexus of sub-cortical systems and other prefrontal regions. Particularly we focus on one of the most recent implications of neuroscientific evidences regarding the OFC - possible functional dissociation between two of its sub-regions : lateral and medial. We present a system-level computational model of decision-making and learning involving the two sub-regions taking into account their individual roles as commonly implicated in neuroscientific studies. We emphasize on the role of the interactions between the sub-regions within the OFC as well as the role of other sub-cortical structures which form a network with them. We leverage well-known computational architecture of thalamo-cortical basal ganglia loops, accounting for recent experimental findings on monkeys with lateral and medial OFC lesions, performing a 3-arm bandit task. First we replicate the seemingly dissociate effects of lesions to lateral and medial OFC during decision-making as a function of value-difference of the presented options. Further we demonstrate and argue that such an effect is not necessarily due to the dissociate roles of both the subregions, but rather a result of complex temporal dynamics between the interacting networks in which they are involved.Author summaryWe first highlight the role of the Orbitofrontal Cortex (OFC) in value-based decision making and goal-directed behavior in primates. We establish the position of OFC at the intersection of cortical mechanisms and thalamo-basal ganglial circuits. In order to understand possible mechanisms through which the OFC exerts emotional control over behavior, among several other possibilities, we consider the case of dissociate roles of two of its topographical subregions - lateral and medial parts of OFC. We gather predominant roles of each of these sub-regions as suggested by numerous experimental evidences in the form of a system-level computational model that is based on existing neuronal architectures. We argue that besides possible dissociation, there could be possible interaction of these sub-regions within themselves and through other sub-cortical structures, in distinct mechanisms of choice and learning. The computational framework described accounts for experimental data and can be extended to more comprehensive detail of representations required to understand the processes of decision-making, learning and the role of OFC and subsequently the regions of prefrontal cortex in general.

Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning

2009 ◽  
Vol 20 (5) ◽  
pp. 578-585 ◽  
Author(s):  
Michael C. Frank ◽  
Noah D. Goodman ◽  
Joshua B. Tenenbaum
Keyword(s):  
Computational Model ◽  
Word Learning ◽  
Word Meaning ◽  
Mutual Exclusivity ◽  
Object Individuation ◽  
Word Meanings ◽  
Inference Problems ◽  
Corpus Data ◽  
Situational Learning

Word learning is a “chicken and egg” problem. If a child could understand speakers' utterances, it would be easy to learn the meanings of individual words, and once a child knows what many words mean, it is easy to infer speakers' intended meanings. To the beginning learner, however, both individual word meanings and speakers' intentions are unknown. We describe a computational model of word learning that solves these two inference problems in parallel, rather than relying exclusively on either the inferred meanings of utterances or cross-situational word-meaning associations. We tested our model using annotated corpus data and found that it inferred pairings between words and object concepts with higher precision than comparison models. Moreover, as the result of making probabilistic inferences about speakers' intentions, our model explains a variety of behavioral phenomena described in the word-learning literature. These phenomena include mutual exclusivity, one-trial learning, cross-situational learning, the role of words in object individuation, and the use of inferred intentions to disambiguate reference.

scholarly journals From Translation Studies and audiovisual translation to media accessibility

Target ◽  
2016 ◽  
Vol 28 (2) ◽  
pp. 248-260 ◽  
Author(s):  
Aline Remael ◽  
Nina Reviers ◽  
Reinhild Vandekerckhove
Keyword(s):  
Speech Recognition ◽  
Basic Research ◽  
Translation Studies ◽  
Hybrid Form ◽  
Audio Description ◽  
Translation Practice ◽  
Recent Developments ◽  
Key Issues ◽  
The One

Abstract Recent developments in Translation Studies and translation practice have not only led to a profusion of approaches, but also to the development of new text forms and translation modes. Media Accessibility, particularly audio description (AD) and subtitling for the deaf and hard-of-hearing (SDH), is an example of such a ‘new’ mode. SDH has been evolving quickly in recent decades and new developments such as interlingual SDH and live subtitling with speech recognition bring it closer to established forms of translation and interpreting. On the one hand, interlingual SDH reintroduces Jakobson’s (1959) ‘translation proper’ while the use of speech recognition has led to the creation of a hybrid form that has affinities with both subtitling and interpreting. Audio description, for its part, cannot even be fitted into Jakobson’s ‘intersemiotic translation’ model since it involves translation from images into words. Research into AD is especially interesting since it rallies methods from adjacent disciplines, much in the same way that Holmes ([1972] 1988) described TS when it was a fledgling discipline. In 2008, Braun set out a research agenda for AD and the wealth of topics and research approaches dealt with in her article illustrate the immense complexity of this field and the work still to be done. Although AD and SDH research have developed at different paces and are concerned with different topics, converging trends do appear. Particularly the role of technology and the concept of multimodality seem to be key issues. This article aims to give an overview of current research trends in both these areas. It illustrates the possibilities of technology-driven research – particularly popular in SDH and live-subtitling research – while at the same time underlining the value of individual, human-driven approaches, which are still the main ‘modus operandi’ in the younger discipline of AD where much basic research is still required.

The Role of Automated Speech Recognition in Endoscopic Data Collection

Endoscopy ◽  
1992 ◽  
Vol 24 (S 2) ◽  
pp. 493-498 ◽  
Author(s):  
R. S. Johannes ◽  
D. L. Carr-Locke
Keyword(s):  
Speech Recognition ◽  
Data Collection ◽  
Automated Speech Recognition
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