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Language development and the features associated with it are of great interest in the field of AI. Ted Gibson, from the TEDLab at MIT, studies why languages look the way they do and explores topics such as the purpose of language, linguistic universals, language comprehension, and processing difficulty. Professor Gibson suggests thinking of language models as theories of language. Language is a complex phenomenon with various factors influencing its structure and development.
Dependency distances play a crucial role in language processing. Longer dependencies between words often lead to increased processing difficulty. Research shows that human languages tend to minimize dependency lengths, making it easier for people to understand and produce sentences. Different languages have different word orders, but they all tend to minimize dependency lengths, regardless of the specific word order. The idea that human languages minimize dependency lengths is supported by the fact that even non-projective languages prioritize local dependencies over longer ones.
Sentence parsing involves two main components: structural integration and memory cost. When encountering a new word, the challenge lies in integrating it into the existing syntactic structure of the sentence. Memory cost refers to the difficulty of holding onto and reconstructing the syntactic structure as new words are encountered. Research suggests that memory cost is influenced by the interference of similar elements and the predictability of words from their context. People tend to remember salient and less predictable elements while reconstructing the rest based on probabilistic syntactic structures.
Language development involves the invention and use of words, influenced by the communicative needs of a particular culture. Different languages prioritize different concepts and invent words to represent those concepts. The presence or absence of words for specific concepts, such as numbers or colors, can impact language processing. For example, some cultures lack words for numbers, challenging the notion that language creates the concept of exact quantity. The Whorf hypothesis, which suggests that language shapes thought, is debated in the context of the relationship between language and numerical cognition.
Language is viewed as a communication system invented by humans to facilitate communication. Evidence from research on brain activity suggests that regions responsible for language processing are distinct from those involved in complex thought. The work of researchers like F. Federenko and Rosmary Varley has shown that these language processing regions in the brain do not overlap with areas involved in other cognitive tasks, indicating that language and thought are separate processes.
To examine the relationship between language and thought, empirical data and quantitative methods are essential. Federenko's research using brain scans demonstrates that the language processing network in the brain is distinct and does not overlap with regions involved in other complex tasks. This finding challenges the notion that language is necessary for all forms of thinking and supports the idea that thought can occur independent of language.
There is evidence that individuals can think without relying on language. Some people lack an inner voice, highlighting that thoughts can be formed without using internalized language. Additionally, an internet poll revealed that a substantial proportion of individuals do not experience an inner voice during their thinking process.
No compelling evidence has been found to support Chomsky's view that language is necessary for intricate thought. The idea that language is required for complex conceptualization lacks empirical support and goes against the evidence that language and thought engage distinct neural networks.
Dependency grammar is a simple and useful approach to understanding language structure. Most utterances can be represented as directed acyclic graphs, with a head and dependencies. This structure helps explain word order patterns across languages. For example, English is a head-initial language, where verbs typically come before their nouns, while Japanese is a head-final language, with nouns following the verb. Dependency length minimization explains why languages prefer close dependencies.
Chomsky's transformational grammar, which incorporates movement and empty categories, has been a prominent linguistic theory. However, there are critiques of this approach. One alternative perspective suggests that there are different functions for words, like the auxiliary verb 'is' in interrogative and declarative sentences. This construction-based approach argues against the necessity of movement. Dependency grammar provides a simpler explanation for language processing and learning. Large language models, despite their differences from human language acquisition, can still serve as theories of human language and offer valuable insights.
In episode 107 of The Gradient Podcast, Daniel Bashir speaks to Professor Ted Gibson.
Ted is a Professor of Cognitive Science at MIT. He leads the TedLab, which investigates why languages look the way they do; the relationship between culture and cognition, including language; and how people learn, represent, and process language.
Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub
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Outline:
* (00:00) Intro
* (02:13) Prof Gibson’s background
* (05:33) The computational linguistics community and NLP, engineering focus
* (10:48) Models of brains
* (12:03) Prof Gibson’s focus on behavioral work
* (12:53) How dependency distances impact language processing
* (14:03) Dependency distances and the origin of the problem
* (18:53) Dependency locality theory
* (21:38) The structures languages tend to use
* (24:58) Sentence parsing: structural integrations and memory costs
* (36:53) Reading strategies vs. ordinary language processing
* (40:23) Legalese
* (46:18) Cross-dependencies
* (50:11) Number as a cognitive technology
* (54:48) Experiments
* (1:03:53) Why counting is useful for Western societies
* (1:05:53) The Whorf hypothesis
* (1:13:05) Language as Communication
* (1:13:28) The noisy channel perspective on language processing
* (1:27:08) Fedorenko lab experiments—language for thought vs. communication and Chomsky’s claims
* (1:43:53) Thinking without language, inner voices, language processing vs. language as an aid for other mental processing
* (1:53:01) Dependency grammars and a critique of Chomsky’s grammar proposals, LLMs
* (2:08:48) LLM behavior and internal representations
* (2:12:53) Outro
Links:
* Re-imagining our theories of language
* Research — linguistic complexity and dependency locality theory
* Linguistic complexity: locality of syntactic dependencies (1998)
* The Dependency Locality Theory: A Distance-Based Theory of Linguistic Complexity (2000)
* Consequences of the Serial Nature of Linguistic Input for Sentential Complexity (2005)
* Large-scale evidence of dependency length minimization in 37 languages (2015)
* Dependency locality as an explanatory principle for word order (2020)
* A resource-rational model of human processing of recursive linguistic structure (2022)
* Research — language processing / communication and cross-linguistic universals
* Number as a cognitive technology: Evidence from Pirahã language and cognition (2008)
* The communicative function of ambiguity in language (2012)
* Color naming across languages reflects color use (2017)
* How Efficiency Shapes Human Language (2019)
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