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Language01:16

Language

891
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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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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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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Low-resource Language Identification of English and Kokborok Code-Mixed Sentences.

Enjula Uchoi1, Koj Sambyo2

  • 1Department of Computer Science & Engineering, National Institute of Technology; enjula.phd23@nitap.ac.in.

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This study introduces an unsupervised model for word-level language detection in low-resource English-Kokborok text. The novel approach achieves 93.15% accuracy, outperforming existing methods for code-mixed language identification.

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Area of Science:

  • Computational Linguistics
  • Natural Language Processing
  • Low-Resource Language Technologies

Background:

  • Multilingual text usage necessitates automatic language detection.
  • Code-switching and code-mixing are prevalent in many languages, including Indian languages.
  • Existing research often overlooks low-resource language pairs.

Purpose of the Study:

  • To develop an unsupervised model for word-level language identification.
  • To address the specific challenge of detecting languages in English-Kokborok code-mixed text.
  • To pioneer language identification for low-resource language pairs.

Main Methods:

  • A hybrid approach combining a frequency dictionary with a character n-gram model.
  • Utilizing the Viterbi technique to integrate a character n-gram Markov model and a frequency lexicon.
  • An unsupervised method designed for low-resource scenarios.

Main Results:

  • Achieved a word-level accuracy of 93.15% for English-Kokborok language identification.
  • Outperformed the BiLSTM-CRF model (88.5%) and a rule-based baseline (85.3%).
  • Demonstrated the efficacy of combining lexicon and statistical methods.

Conclusions:

  • The proposed unsupervised model is effective for word-level language detection in low-resource settings.
  • Combining lexicon and statistical approaches is a viable strategy for low-resource languages.
  • This work provides a foundational method for analyzing code-mixed text in previously unaddressed language pairs.