scholarly journals Parallel processing in speech perception: Local and global representations of linguistic context

2021 ◽  
Author(s):  
Christian Brodbeck ◽  
Shohini Bhattasali ◽  
Aura A L Cruz Heredia ◽  
Philip Resnik ◽  
Jonathan Z Simon ◽  
...  
Keyword(s):  
Speech Processing ◽  
Predictive Models ◽  
Local Context ◽  
Linguistic Context ◽  
Neural Responses ◽  
Temporal Lobes ◽  
Sentence Level ◽  
Available Information ◽  
Context Models ◽  
Context Free

Speech processing is highly incremental. It is widely accepted that listeners continuously use the linguistic context to anticipate upcoming concepts, words and phonemes. However, previous evidence supports two seemingly contradictory models of how predictive cues are integrated with bottom-up evidence: Classic psycholinguistic paradigms suggest a two-stage model, in which acoustic input is represented fleetingly in a local, context-free manner, but quickly integrated with contextual constraints. This contrasts with the view that the brain constructs a single unified interpretation of the input, which fully integrates available information across representational hierarchies and predictively modulates even earliest sensory representations. To distinguish these hypotheses, we tested magnetoencephalography responses to continuous narrative speech for signatures of unified and local predictive models. Results provide evidence for some aspects of both. Local context models, one based on sublexical phoneme sequences, and one based on the phonemes in the current word alone, do uniquely predict some part of early neural responses; 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 non-identical parts of the superior temporal lobes bilaterally, although the more local models tend to be right-lateralized. 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.

scholarly journals Speech Processing Disorder in Neural Hearing Loss

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Joseph P. Pillion
Keyword(s):  
Speech Processing ◽  
Auditory Processing ◽  
Neurological Disorders ◽  
Auditory Neuropathy ◽  
Central Auditory Processing ◽  
Temporal Lobes ◽  
Electrophysiological Tests ◽  
Bilateral Lesions ◽  
Clinical Conditions ◽  
Inferior Colliculi

Deficits in central auditory processing may occur in a variety of clinical conditions including traumatic brain injury, neurodegenerative disease, auditory neuropathy/dyssynchrony syndrome, neurological disorders associated with aging, and aphasia. Deficits in central auditory processing of a more subtle nature have also been studied extensively in neurodevelopmental disorders in children with learning disabilities, ADD, and developmental language disorders. Illustrative cases are reviewed demonstrating the use of an audiological test battery in patients with auditory neuropathy/dyssynchrony syndrome, bilateral lesions to the inferior colliculi, and bilateral lesions to the temporal lobes. Electrophysiological tests of auditory function were utilized to define the locus of dysfunction at neural levels ranging from the auditory nerve, midbrain, and cortical levels.

scholarly journals Collaboration Age

2020 ◽  
Author(s):  
Maurizio Busacca ◽  
Roberto Paladini
Keyword(s):  
Third Sector ◽  
Production Method ◽  
Local Context ◽  
Essential Condition ◽  
Hybrid Solutions ◽  
Strategic Role ◽  
And Function ◽  
Available Information ◽  
The Empirical Analysis

Recently, public policies of urban regeneration have intensified and multiplied. They are being promoted with the aim to start social and economic dynamics within the local context which is subject to intervention. From the empirical analysis, we realise that such activities are mainly implemented by three subjects or by mixed coalitions (public institutions, actors of the third sector and companies). Within them, each player is moved by a multiplicity of interests and goals that go beyond their own nature – public interest, market and mutualism – and tend to redefine themselves, thus becoming hybrid forms of production of value (social, economic, cultural). By studying a number Italian and Catalan cases, this essay deals with the theory that, under specific conditions and configurations, a collaborative direction – of organization, production and design – would give life to successful procedures, even without the identification of a one-best-way. The collaboration is not simply a choice of operation, but a real production method which mobilises social resources to create hybrid solutions – between state, market and society – to complex issues that could not be faced solely with the use of the rationale of action of one among the three actors. In this framework, the systems of relations and interactions between players and shared capital become an essential condition for the success of every initiative of urban redevelopment, or failure thereof. Such initiatives are brought to life by the strategic role of individuals who foster connections as well as the dissemination of non-redundant information between social networks, and collective and individual actors which would otherwise be separated and barely able to communicate and collaborate with each other. In addition to the functions carried out by knowledge brokers, that have been extensively described in organisational studies and economic sociology, the aforementioned figures act as real social enzymes, that is to say, they handle the available information and function as catalysts of social processes of production of knowledge. Moreover, they increase the reaction speed, working on mechanisms which control the spontaneity.

scholarly journals Hearing loss is associated with delayed neural responses to continuous speech

2021 ◽  
Author(s):  
Marlies Gillis ◽  
Lien Decruy ◽  
Jonas Vanthornhout ◽  
Tom Francart
Keyword(s):  
Hearing Loss ◽  
Speech Processing ◽  
Noise Level ◽  
Normal Hearing ◽  
Hearing Impaired ◽  
Neural Responses ◽  
Continuous Speech ◽  
Processing Efficiency ◽  
Sound Amplification ◽  
The Impact

AbstractWe investigated the impact of hearing loss on the neural processing of speech. Using a forward modelling approach, we compared the neural responses to continuous speech of 14 adults with sensorineural hearing loss with those of age-matched normal-hearing peers.Compared to their normal-hearing peers, hearing-impaired listeners had increased neural tracking and delayed neural responses to continuous speech in quiet. The latency also increased with the degree of hearing loss. As speech understanding decreased, neural tracking decreased in both population; however, a significantly different trend was observed for the latency of the neural responses. For normal-hearing listeners, the latency increased with increasing background noise level. However, for hearing-impaired listeners, this increase was not observed.Our results support that the neural response latency indicates the efficiency of neural speech processing. Hearing-impaired listeners process speech in silence less efficiently then normal-hearing listeners. Our results suggest that this reduction in neural speech processing efficiency is a gradual effect which occurs as hearing deteriorates. Moreover, the efficiency of neural speech processing in hearing-impaired listeners is already at its lowest level when listening to speech in quiet, while normal-hearing listeners show a further decrease in efficiently when the noise level increases.From our results, it is apparent that sound amplification does not solve hearing loss. Even when intelligibility is apparently perfect, hearing-impaired listeners process speech less efficiently.

scholarly journals Drug-Drug Interaction Extraction via Recurrent Hybrid Convolutional Neural Networks with an Improved Focal Loss

Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 37 ◽  
Author(s):  
Xia Sun ◽  
Ke Dong ◽  
Long Ma ◽  
Richard Sutcliffe ◽  
Feijuan He ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Loss Function ◽  
Contextual Information ◽  
Imbalanced Data ◽  
Biomedical Literature ◽  
Local Context ◽  
Automatic Extraction ◽  
Sentence Level ◽  
Interaction Extraction

Drug-drug interactions (DDIs) may bring huge health risks and dangerous effects to a patient’s body when taking two or more drugs at the same time or within a certain period of time. Therefore, the automatic extraction of unknown DDIs has great potential for the development of pharmaceutical agents and the safety of drug use. In this article, we propose a novel recurrent hybrid convolutional neural network (RHCNN) for DDI extraction from biomedical literature. In the embedding layer, the texts mentioning two entities are represented as a sequence of semantic embeddings and position embeddings. In particular, the complete semantic embedding is obtained by the information fusion between a word embedding and its contextual information which is learnt by recurrent structure. After that, the hybrid convolutional neural network is employed to learn the sentence-level features which consist of the local context features from consecutive words and the dependency features between separated words for DDI extraction. Lastly but most significantly, in order to make up for the defects of the traditional cross-entropy loss function when dealing with class imbalanced data, we apply an improved focal loss function to mitigate against this problem when using the DDIExtraction 2013 dataset. In our experiments, we achieve DDI automatic extraction with a micro F-score of 75.48% on the DDIExtraction 2013 dataset, outperforming the state-of-the-art approach by 2.49%.

scholarly journals A Statistical Parsing Framework for Sentiment Classification

2015 ◽  
Vol 41 (2) ◽  
pp. 293-336 ◽  
Author(s):  
Li Dong ◽  
Furu Wei ◽  
Shujie Liu ◽  
Ming Zhou ◽  
Ke Xu
Keyword(s):  
Sentiment Analysis ◽  
Sentiment Classification ◽  
Training Data ◽  
Data Sets ◽  
Syntactic Parsing ◽  
Benchmark Data ◽  
Sentence Level ◽  
Statistical Parsing ◽  
Parse Trees ◽  
Context Free

We present a statistical parsing framework for sentence-level sentiment classification in this article. Unlike previous works that use syntactic parsing results for sentiment analysis, we develop a statistical parser to directly analyze the sentiment structure of a sentence. We show that complicated phenomena in sentiment analysis (e.g., negation, intensification, and contrast) can be handled the same way as simple and straightforward sentiment expressions in a unified and probabilistic way. We formulate the sentiment grammar upon Context-Free Grammars (CFGs), and provide a formal description of the sentiment parsing framework. We develop the parsing model to obtain possible sentiment parse trees for a sentence, from which the polarity model is proposed to derive the sentiment strength and polarity, and the ranking model is dedicated to selecting the best sentiment tree. We train the parser directly from examples of sentences annotated only with sentiment polarity labels but without any syntactic annotations or polarity annotations of constituents within sentences. Therefore we can obtain training data easily. In particular, we train a sentiment parser, s.parser, from a large amount of review sentences with users' ratings as rough sentiment polarity labels. Extensive experiments on existing benchmark data sets show significant improvements over baseline sentiment classification approaches.

scholarly journals Differential neural mechanisms for early and late prediction error detection

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Rahim Malekshahi ◽  
Anil Seth ◽  
Amalia Papanikolaou ◽  
Zenon Mathews ◽  
Niels Birbaumer ◽  
...  
Keyword(s):  
Error Detection ◽  
Predictive Models ◽  
Visual Processing ◽  
Prediction Error ◽  
Early Stage ◽  
Predictive Coding ◽  
Representational Content ◽  
Saccadic Eye Movements ◽  
Spatial Prediction ◽  
Neural Responses

Abstract Emerging evidence indicates that prediction, instantiated at different perceptual levels, facilitate visual processing and enable prompt and appropriate reactions. Until now, the mechanisms underlying the effect of predictive coding at different stages of visual processing have still remained unclear. Here, we aimed to investigate early and late processing of spatial prediction violation by performing combined recordings of saccadic eye movements and fast event-related fMRI during a continuous visual detection task. Psychophysical reverse correlation analysis revealed that the degree of mismatch between current perceptual input and prior expectations is mainly processed at late rather than early stage, which is instead responsible for fast but general prediction error detection. Furthermore, our results suggest that conscious late detection of deviant stimuli is elicited by the assessment of prediction error’s extent more than by prediction error per se. Functional MRI and functional connectivity data analyses indicated that higher-level brain systems interactions modulate conscious detection of prediction error through top-down processes for the analysis of its representational content, and possibly regulate subsequent adaptation of predictive models. Overall, our experimental paradigm allowed to dissect explicit from implicit behavioral and neural responses to deviant stimuli in terms of their reliance on predictive models.

scholarly journals Neural specializations for speech and pitch: moving beyond the dichotomies

2007 ◽  
Vol 363 (1493) ◽  
pp. 1087-1104 ◽  
Author(s):  
Robert J Zatorre ◽  
Jackson T Gandour
Keyword(s):  
Speech Processing ◽  
Integrated Approach ◽  
General Purpose ◽  
Speech Sounds ◽  
Neural Responses ◽  
Afferent Pathways ◽  
Acoustical Properties ◽  
Domain Specific ◽  
Auditory Cortices ◽  
Processing Mechanisms

The idea that speech processing relies on unique, encapsulated, domain-specific mechanisms has been around for some time. Another well-known idea, often espoused as being in opposition to the first proposal, is that processing of speech sounds entails general-purpose neural mechanisms sensitive to the acoustic features that are present in speech. Here, we suggest that these dichotomous views need not be mutually exclusive. Specifically, there is now extensive evidence that spectral and temporal acoustical properties predict the relative specialization of right and left auditory cortices, and that this is a parsimonious way to account not only for the processing of speech sounds, but also for non-speech sounds such as musical tones. We also point out that there is equally compelling evidence that neural responses elicited by speech sounds can differ depending on more abstract, linguistically relevant properties of a stimulus (such as whether it forms part of one's language or not). Tonal languages provide a particularly valuable window to understand the interplay between these processes. The key to reconciling these phenomena probably lies in understanding the interactions between afferent pathways that carry stimulus information, with top-down processing mechanisms that modulate these processes. Although we are still far from the point of having a complete picture, we argue that moving forward will require us to abandon the dichotomy argument in favour of a more integrated approach.

Toward understanding the problem in severely disabled readers Part 1: Vowel errors

1989 ◽  
Vol 10 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Susan E. Bryson ◽  
Janet F. Werker
Keyword(s):  
Phonological Processing ◽  
Reading Level ◽  
Local Context ◽  
Linguistic Processing ◽  
The Disabled ◽  
Context Dependent ◽  
Disabled Readers ◽  
And Performance ◽  
Phonemic Level ◽  
Context Free

ABSTRACTThis experiment examined the vowel responses of severely disabled readers and normal control children in reading orthographically regular nonwords. The disabled readers were divided into three groups based on their relative Verbal and Performance IQs. Following the rationale of Fowler, Shankweiler, and Liberman (1979), vowel responses were classified as incorrect or correct. Correctness was determined according to either context-free or context-dependent criteria. The main finding was that the vowel responses of two out of three reading disabled groups paralleled those of their reading level peers. However, disabled readers with higher Performance than Verbal IQs made significantly more context-free responses and significantly fewer context-dependent responses than all other groups. Moreover, knowledge of how speech is segmented at the phonemic level predicted performance on the reading task. The findings suggest that disabled readers employ very local (context-independent) strategies in reading; these findings are discussed in terms of the idea that disabled readers suffer a basic deficit in phonological processing (Liberman, Liberman, & Mattingly, 1980) or linguistic processing (Siegel & Ryan, 1984).

Discourse Analysis and Grammar Instruction

1990 ◽  
Vol 11 ◽  
pp. 135-151 ◽  
Author(s):  
Marianne Celce-Murcia
Keyword(s):  
Discourse Analysis ◽  
Native Speakers ◽  
Grammar Instruction ◽  
Sentence Level ◽  
Speakers Of Other Languages ◽  
Native Speakers Of English ◽  
State Of Affairs ◽  
Context Free

Only relatively recently has discourse analysis begun to have an impact on how English grammer (i.e., the rules of morphology and syntax) is taught to non-native speakers of English. In fact, a majority of teachers of English to speakers of other languages still conceive of grammer, and thus teach grammer, as a sentence-level phenomenon (if and when they teach it). This state-of-affairs reflects a rather counterproductive view of grammer since, as Bolinger (1968; 1977) has long argued, there are relatively few rules of English grammer that are completely context-free.

Sign in / Sign up

Export Citation Format

Share Document