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Related Concept Videos

Language01:16

Language

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Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
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What is Natural Selection?01:32

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Natural selection is an evolutionary process in which individuals with survival-promoting traits reproduce at higher rates. These favorable traits become more common within a population or species. Naturally selected traits initially arise via random genetic mutations. In order for selection to occur, there must be variation within a population, the trait controlling the variation must be heritable, and there must be an evolutionary advantage for variation in the trait.
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Components of Language01:24

Components of Language

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Language Development01:22

Language Development

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
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Language and Cognition01:27

Language and Cognition

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Nature and Nurture

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Many human characteristics, like height, are shaped by both nature—in other words, by our genes—and by nurture, or our environment. For example, chronic stress during childhood inhibits the production of growth hormones and consequently reduces bone growth and height. Scientists estimate that 70-90% of variation in height is due to genetic differences among individuals, and 10-30% of variation in height is due to differences in the environments that individuals experience,...
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[Deep Learning and Natural Language Processing].

Yoshimasa Tsuruoka1

  • 1Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo.

Brain and Nerve = Shinkei Kenkyu No Shinpo
|January 11, 2019
PubMed
Summary
This summary is machine-generated.

Deep learning techniques have revolutionized natural language processing (NLP), enabling advanced capabilities in tasks like machine translation. This overview explores current deep learning-based NLP technologies and their applications.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Computational Linguistics

Background:

  • Natural Language Processing (NLP) has experienced significant advancements.
  • Deep learning techniques have become central to these recent breakthroughs.

Purpose of the Study:

  • To provide a concise introduction to deep learning.
  • To offer an overview of current deep learning-based NLP technologies.

Main Methods:

  • Review of general neural network models.
  • Explanation of recurrent neural networks.
  • Discussion of attention mechanisms.

Main Results:

  • Deep learning models can be combined to perform complex NLP tasks.
  • Syntactic parsing, machine translation, and summarization are examples of achievable tasks.

Conclusions:

  • Deep learning has transformed the capabilities of NLP.
  • Current deep learning-based NLP technology offers powerful solutions for various language understanding and generation problems.