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Related Concept Videos

Components of Language01:24

Components of Language

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. “eh”). Phonemes combine to...
Language and Cognition01:27

Language and Cognition

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.
Language Development01:22

Language Development

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...
Language01:16

Language

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...
Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

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...
Introduction to Language of Pathophysiology ll01:17

Introduction to Language of Pathophysiology ll

This lesson explores key terms that describe how diseases progress, their outcomes, and their distribution in populations.Diagnostic tests identify diseases and monitor treatment. These include blood and urine tests, biopsies, imaging (X-ray, MRI), and detection of infectious agents.Remission is a reduction or disappearance of symptoms.Exacerbation refers to the worsening of symptoms, such as increased wheezing during an asthma attack.A precipitating factor triggers an acute episode, while a...

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Related Experiment Videos

Linguists should learn to love speech-based deep learning models.

Marianne de Heer Kloots1, Paul Boersma2, Willem Zuidema1

  • 1Institute for Logic, Language and Computation (ILLC), University of Amsterdam, Amsterdam, Netherlands m.l.s.deheerkloots@uva.nl.

The Behavioral and Brain Sciences
|June 30, 2026
PubMed
Summary
This summary is machine-generated.

This study highlights limitations in text-based Large Language Models (LLMs) for linguistic research. It proposes that audio-based deep learning models offer greater potential for understanding human language beyond written text.

Related Experiment Videos

Area of Science:

  • Cognitive Science
  • Artificial Intelligence
  • Computational Linguistics

Background:

  • A framework exists bridging deep learning and linguistic theories.
  • Current research often focuses on text-based Large Language Models (LLMs).
  • LLMs' text-centric nature limits their scope in linguistic inquiry.

Purpose of the Study:

  • To critique the limitations of generative text-based LLMs in linguistics.
  • To advocate for the integration of audio-based deep learning models in language research.
  • To expand the scope of computational linguistics beyond written text.

Main Methods:

  • Conceptual analysis of existing frameworks.
  • Comparative evaluation of text-based vs. audio-based deep learning models.
  • Argumentation for the utility of auditory data in language models.

Main Results:

  • Text-based LLMs inadequately capture the full spectrum of human language phenomena.
  • Audio-based deep learning models present a more comprehensive approach to linguistic analysis.
  • Significant linguistic questions remain unaddressed by current text-only models.

Conclusions:

  • The focus on text-based LLMs restricts meaningful interaction between AI and linguistics.
  • Audio-based deep learning models are essential for a more complete understanding of human language.
  • Future research should prioritize auditory data processing in AI for linguistic insights.