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Digital Approaches to Analyzing and Translating Emotion: What Is Love? ...
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Digital Approaches to Analyzing and Translating Emotion: What Is Love? ...
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The Influence of Multilingualism and Mutual Intelligibility on Wikipedia Reading Behaviour: A Research Proposal ...
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Loose and tight languages: A typology based on associations between constructions and lexemes ...
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Loose and tight languages: A typology based on associations between constructions and lexemes ...
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A Refutation of Finite-State Language Models through Zipf’s Law for Factual Knowledge
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In: Entropy ; Volume 23 ; Issue 9 (2021)
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Abstract:
We present a hypothetical argument against finite-state processes in statistical language modeling that is based on semantics rather than syntax. In this theoretical model, we suppose that the semantic properties of texts in a natural language could be approximately captured by a recently introduced concept of a perigraphic process. Perigraphic processes are a class of stochastic processes that satisfy a Zipf-law accumulation of a subset of factual knowledge, which is time-independent, compressed, and effectively inferrable from the process. We show that the classes of finite-state processes and of perigraphic processes are disjoint, and we present a new simple example of perigraphic processes over a finite alphabet called Oracle processes. The disjointness result makes use of the Hilberg condition, i.e., the almost sure power-law growth of algorithmic mutual information. Using a strongly consistent estimator of the number of hidden states, we show that finite-state processes do not satisfy the Hilberg condition whereas Oracle processes satisfy the Hilberg condition via the data-processing inequality. We discuss the relevance of these mathematical results for theoretical and computational linguistics.
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Keyword:
algorithmic mutual information; hidden Markov processes; Hilberg’s hypothesis; perigraphic processes; statistical language modeling; Zipf’s law
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URL: https://doi.org/10.3390/e23091148
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Analyzing brain networks in language and social tasks using data-driven approaches
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Multi-Word Terminology Extraction and Its Role in Document Embedding
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In: Electronic Theses and Dissertations (2021)
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The necessity modals have to, must, need to and should: using n-grams to help identify common and distinct semantic and pragmatic aspects. 11.2: 220-243
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In: ISSN: 1876-1933 ; EISSN: 1876-1941 ; Constructions and Frames ; https://hal.archives-ouvertes.fr/hal-02369306 ; Constructions and Frames, John Benjamins, 2019, 11, pp.220 - 243. ⟨10.1075/cf.00029.cap⟩ (2019)
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The necessity modals have to, must, need to and should: using n-grams to help identify common and distinct semantic and pragmatic aspects
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In: ISSN: 1876-1933 ; EISSN: 1876-1941 ; Constructions and Frames ; https://hal.archives-ouvertes.fr/hal-02501498 ; Constructions and Frames, John Benjamins, 2019, 11 (2), pp.220-243. ⟨10.1075/cf.00029.cap⟩ (2019)
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Unique information via dependency constraints
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In: Journal of Physics A: Mathematical and Theoretical, vol 52, iss 1 (2019)
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Information Across the Ecological Hierarchy
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In: Entropy ; Volume 21 ; Issue 10 (2019)
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Complexity Measures of Voice Recordings as a Discriminative Tool for Parkinson’s Disease
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In: Biosensors ; Volume 10 ; Issue 1 (2019)
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