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  2. Attention (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Attention_(machine_learning)

    During the deep learning era, attention mechanism was developed to solve similar problems in encoding-decoding. [1] In machine translation, the seq2seq model, as it was proposed in 2014, [24] would encode an input text into a fixed-length vector, which would then be decoded into an output text. If the input text is long, the fixed-length vector ...

  3. Noticing hypothesis - Wikipedia

    en.wikipedia.org/wiki/Noticing_hypothesis

    It is exclusive from attention and understanding, and has been criticized within the field of psychology and second language acquisition. Schmidt and Frota studied noticing in Schmidt as a Portuguese language learner and collected their findings through diary study and audio recordings. The hypothesis was modified in 1994 in light of criticism.

  4. Word recognition - Wikipedia

    en.wikipedia.org/wiki/Word_recognition

    Parallel letter recognition is the most widely accepted model of word recognition by psychologists today. [3] In this model, all letters within a group are perceived simultaneously for word recognition. In contrast, the serial recognition model proposes that letters are recognized individually, one by one, before being integrated for word ...

  5. Missing letter effect - Wikipedia

    en.wikipedia.org/wiki/Missing_letter_effect

    The missing letter effect is more likely to appear when reading words that are part of a normal sequence, than when words are embedded in a mixed-up sequence (e.g. readers asked to read backwards). [5] Despite the missing letter effect being a common phenomenon, there are different factors that have influence on the magnitude of this effect.

  6. Interaction hypothesis - Wikipedia

    en.wikipedia.org/wiki/Interaction_hypothesis

    Similar to Krashen's input hypothesis, the interaction hypothesis claims that comprehensible input, which is characterized as a variety of language that can be understood by a learner, [3] is important for language learning. There are a number of ways in which input may be modified for the benefit of the learner.

  7. Artificial grammar learning - Wikipedia

    en.wikipedia.org/wiki/Artificial_grammar_learning

    Artificial grammar learning (AGL) is a paradigm of study within cognitive psychology and linguistics.Its goal is to investigate the processes that underlie human language learning by testing subjects' ability to learn a made-up grammar in a laboratory setting.

  8. Glossary of language education terms - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_language...

    They should not over-explain or make things too easy. Learning comes through discovery. Language skills In language teaching, this refers to the mode or manner in which language is used. Listening, speaking, reading and writing are generally called the four language skills. Speaking and writing are the productive skills, while reading and ...

  9. Statistical language acquisition - Wikipedia

    en.wikipedia.org/wiki/Statistical_Language...

    Statistical language acquisition, a branch of developmental psycholinguistics, studies the process by which humans develop the ability to perceive, produce, comprehend, and communicate with natural language in all of its aspects (phonological, syntactic, lexical, morphological, semantic) through the use of general learning mechanisms operating on statistical patterns in the linguistic input.