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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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Components of Language01:24

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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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Higher Mental Functions of the Brain: Language01:10

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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Related Experiment Video

Updated: Jan 29, 2026

Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition
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Comparing neural- and N-gram-based language models for word segmentation.

Yerai Doval1, Carlos Gómez-Rodríguez2

  • 1Grupo COLE, Departamento de Informática E.S. de Enxeñaría Informática Universidade de Vigo Campus As Lagoas Ourense 32004 Spain.

Journal of the Association for Information Science and Technology
|February 19, 2019
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Summary

This study introduces a novel word segmentation system using beam search and byte-level language models. The system effectively handles data sparsity in microtexts, outperforming existing tools.

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Area of Science:

  • Natural Language Processing
  • Computational Linguistics

Background:

  • Word segmentation is crucial for text processing, especially for languages lacking explicit word boundaries.
  • Microtexts present unique challenges due to data sparsity and informal language.

Purpose of the Study:

  • To develop an effective word segmentation system for microtext normalization.
  • To improve upon existing word segmentation tools like Microsoft's Word Breaker and Grant Jenks' WordSegment.

Main Methods:

  • A beam search algorithm combined with a byte/character-level language model (n-gram or recurrent neural network).
  • The system processes text token by token (character or byte) to determine word boundaries.
  • Focus on addressing data sparsity inherent in microtext.

Main Results:

  • The proposed system successfully segmented microtexts.
  • Performance metrics indicate the system met its objectives in precision and efficiency.
  • Outperformed two established word segmentation systems in tests.

Conclusions:

  • The developed word segmentation approach is effective for microtext normalization.
  • The system demonstrates potential for handling data sparsity and improving text processing accuracy.
  • Future work will focus on further enhancing precision and efficiency.