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  2. Context (linguistics) - Wikipedia

    en.wikipedia.org/wiki/Context_(linguistics)

    It can be said then that mutual knowledge, co-text, genre, speakers, hearers create a neurolinguistic composition of context. [ 3 ] Traditionally, in sociolinguistics , social contexts were defined in terms of objective social variables, such as those of class, gender, age or race.

  3. Text world theory - Wikipedia

    en.wikipedia.org/wiki/Text_world_theory

    Text world theory and schema theory seek to help people understand how we process language and create mental representations when we read or listen to something. [1] This theory figuratively describes a piece of language (such as a text, a speech or conversation) as a "world" that the reader, hearer or interlocutor must "build" in their mind. [2]

  4. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity .

  5. Semantic similarity - Wikipedia

    en.wikipedia.org/wiki/Semantic_similarity

    Based on text analyses, semantic relatedness between units of language (e.g., words, sentences) can also be estimated using statistical means such as a vector space model to correlate words and textual contexts from a suitable text corpus. The evaluation of the proposed semantic similarity / relatedness measures are evaluated through two main ways.

  6. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The word with embeddings most similar to the topic vector might be assigned as the topic's title, whereas far away word embeddings may be considered unrelated. As opposed to other topic models such as LDA, top2vec provides canonical ‘distance’ metrics between two topics, or between a topic and another embeddings (word, document, or ...

  8. Speech corpus - Wikipedia

    en.wikipedia.org/wiki/Speech_corpus

    A speech corpus (or spoken corpus) is a database of speech audio files and text transcriptions. In speech technology , speech corpora are used, among other things, to create acoustic models (which can then be used with a speech recognition or speaker identification engine). [ 1 ]

  9. Text, Speech and Dialogue - Wikipedia

    en.wikipedia.org/wiki/Text,_Speech_and_Dialogue

    Text, Speech and Dialogue (TSD) is an annual conference involving topics on natural language processing and computational linguistics. The meeting is held every September alternating in Brno and Plzeƈ, Czech Republic. The first Text, Speech and Dialogue conference took place in Brno in 1998.

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