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    AuthorPurver, M (15)Zubiaga, A (6)Alkhalifa, R (5)Chen, X (5)Gan, Y (5)Sadrzadeh, M (5)Huang, Q (3)Liakata, M (3)Armendariz, CS (2)Gkoumas, D (2)... View MoreSubject
    cs.CL (24)
    I.2.7 (4)cs.AI (3)03B65 (2)cs.SI (2)math.CT (2)cs.CL, cs.AI, math.CT (1)cs.DL (1)cs.IR (1)cs.LG (1)... View MoreDate Issued2023 (2)2022 (3)2021 (9)2020 (3)2019 (1)
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    A Generalised Quantifier Theory of Natural Language in Categorical Compositional Distributional Semantics with Bialgebras 

    Hedges, J; Sadrzadeh, M
    Categorical compositional distributional semantics is a model of natural language; it combines the statistical vector space models of words with the compositional models of grammar. We formalise in this model the generalised ...
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    Exploring Semantic Incrementality with Dynamic Syntax and Vector Space Semantics 

    Sadrzadeh, M; Purver, M; Hough, J; Kempson, R; AixDial: the 22nd SemDial Workshop on the Semantics and Pragmatics of Dialogue
    One of the fundamental requirements for models of semantic processing in dialogue is incrementality: a model must reflect how people interpret and generate language at least on a word-by-word basis, and handle phenomena ...
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    Open System Categorical Quantum Semantics in Natural Language Processing 

    Piedeleu, R; Kartsaklis, D; Coecke, B; Sadrzadeh, M
    Originally inspired by categorical quantum mechanics (Abramsky and Coecke, LiCS'04), the categorical compositional distributional model of natural language meaning of Coecke, Sadrzadeh and Clark provides a conceptually ...
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    Linguistic Matrix Theory 

    Kartsaklis, D; Ramgoolam, S; Sadrzadeh, M
    Recent research in computational linguistics has developed algorithms which associate matrices with adjectives and verbs, based on the distribution of words in a corpus of text. These matrices are linear operators on a ...
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    Static and Dynamic Vector Semantics for Lambda Calculus Models of Natural Language 

    Sadrzadeh, M; Muskens, R
    Vector models of language are based on the contextual aspects of language, the distributions of words and how they co-occur in text. Truth conditional models focus on the logical aspects of language, compositional properties ...
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    Temporal Mental Health Dynamics on Social Media 

    Tabak, T; Purver, M; NLP COVID-19 Workshop at EMNLP (ACL, 2020)
    We describe a set of experiments for building a temporal mental health dynamics system. We utilise a pre-existing methodology for distant-supervision of mental health data mining from social media platforms and deploy the ...
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    Alzheimer's Dementia Recognition Using Acoustic, Lexical, Disfluency and Speech Pause Features Robust to Noisy Inputs 

    Rohanian, M; Hough, J; Purver, M; Interspeech
    We present two multimodal fusion-based deep learning models that consume ASR transcribed speech and acoustic data simultaneously to classify whether a speaker in a structured diagnostic task has Alzheimer's Disease and to ...
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    Evaluation of contextual embeddings on less-resourced languages 

    Ulčar, M; Žagar, A; Armendariz, CS; Repar, A; Pollak, S; Purver, M; Robnik-Šikonja, M (2021)
    The current dominance of deep neural networks in natural language processing is based on contextual embeddings such as ELMo, BERT, and BERT derivatives. Most existing work focuses on English; in contrast, we present here ...
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    Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model 

    Zosa, E; Shekhar, R; Karan, M; Purver, M (2021)
    Moderation of reader comments is a significant problem for online news platforms. Here, we experiment with models for automatic moderation, using a dataset of comments from a popular Croatian newspaper. Our analysis shows ...
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    A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis 

    Gkoumas, D; Wang, B; Tsakalidis, A; Wolters, M; Zubiaga, A; Purver, M; Liakata, M (2021)
    Dementia is a family of neurogenerative conditions affecting memory and cognition in an increasing number of individuals in our globally aging population. Automated analysis of language, speech and paralinguistic indicators ...
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