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Related Concept Videos

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 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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Language Development01:22

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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.
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Language01:16

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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.
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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...
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Updated: Feb 24, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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Writer identification: A comparative study across three world major languages.

Gloria Jennis Tan1, Ghazali Sulong1, Mohd Shafry Mohd Rahim1

  • 1Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia; School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, Terengganu, Malaysia.

Forensic Science International
|August 27, 2017
PubMed
Summary
This summary is machine-generated.

This review covers writer identification methods for English, Chinese, and Arabic texts from 2011-2016. While English and Arabic showed progress, Chinese writer identification lagged due to its complex script and dataset limitations.

Keywords:
Chinese handwriting writer recognitionHandwriting identificationText-independent writer recognition

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Area of Science:

  • Computer Science
  • Pattern Recognition
  • Forensic Science

Background:

  • Offline text-independent writer identification is crucial for forensic analysis.
  • Existing literature reviews often focus on single languages or broader timeframes.
  • A comparative analysis across major languages like English, Chinese, and Arabic is needed.

Purpose of the Study:

  • To review and categorize state-of-the-art offline text-independent writer identification techniques.
  • To compare the advancements in writer identification for English, Chinese, and Arabic languages between 2011 and 2016.
  • To identify challenges and limitations in current methodologies, particularly concerning dataset size and language complexity.

Main Methods:

  • Literature review of scientific papers published between 2011 and 2016.
  • Categorization of writer identification techniques into texture-based, structure-based, and allograph-based methods.
  • Comparative analysis of method performance across different languages and datasets.

Main Results:

  • Significant progress was observed in writer identification for English and Arabic texts during the review period.
  • Writer identification for Chinese texts showed slower progress compared to English and Arabic, attributed to its complex writing system.
  • The accuracy of writer identification methods generally decreases with an increase in the size of the utilized dataset.

Conclusions:

  • The state-of-the-art in writer identification has advanced, but disparities exist across languages.
  • The complexity of the Chinese writing system presents a significant challenge for current identification techniques.
  • Dataset limitations and scalability issues need to be addressed for more robust and accurate writer identification systems.