Input-based Phonological Acquisition (Outstanding Dissertations in Linguistics)


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There is an infinite amount of different sounds spanning both frequency domain and time domain , but our brain chunks and classifies the continuous input of sound to something more tangible, into a finite amount of categories. To be sure, phonemes are not letters or anything graphical or anything related to writing , but abstract categories that form the low-level basic units of a language. Especially spoken language. Phonemes are language-specific. The phonemes of English are different from the phonemes of Finnish and those are different from the phonemes of Japanese.

Heck, forget about borders and exemplars, they are just special cases anyway; the distribution of sounds is different. These postures and resonances are similar enough between speakers that we can generalise our ability to recognise vowels even if we hear the voice of that particular speaker for the first time. Now, Japanese uses clusters or categories like presented above for its vowels. But other languages might use entirely different categories.

That raises the question: when we learn another languages, how do we learn novel phonemes with their associated sound distributions? That is an empirical question, and it is studied in the field of second language acquisition research, SLA for short. After parsing the limitless sea of possible sounds into a limited and categorical assortment of phonemes, we then further parse those into words. Or morphemes, linguistically speaking. To be able to do that, we have to possess some kind of a mental lexicon ; a database in the brain that maps strings of phonemes there may possibly be some intermediate representations that chunk phonemes together to help them form more organised patterns: moras, syllables, metrical foots etc.

The formal features are like tags that are further used to understand how the morphemes relate to each other when parsing goes on.

Is “perceptual category” different from “phonemic category?”

Now, I hear the voices of some sceptics. Are phonemes even real? What if the words are stored directly as audio patterns in the brain? In other words, people are insensitive of sounds within the phoneme categories, but very sensitive at or over the borders of phoneme categories. How that learning happens? That — again—is an empirical question. Note that there is a huge amount of individual variability and a lots of factors affecting this.

Nothing is simple in SLA. There is empirical evidence that pronunciation of second language hinges on the perception of the phonetic categories; unless you are able to perceive and distinguish the phonetic categories more or less like a native speaker would, you will have little hope of pronouncing sounds in those categories right, except by chance.

Input-based Phonological Acquisition - Tania Zamuner - Google книги

That means letting the automatised processes in the internal linguistic system to manage the details of the linguistic processing such as forming sounds. Succintly said: output depends on input. Not surprisingly, there has been multiple attempts to teach people to perceive the phonemic categories of the target language and to try and overcome the seemingly difficult task of re-adjusting the phonetic system.

After Logan and Lively , there has been a flurry of studies on a training paradigm called high variability training. These studies have successfully demonstrated perception of novel perceptual categories. They have also demonstrated that this learned categorical knowledge can transfer from perception to pronunciation. So… huzzah, our foreign accent problem is solved! Alas, things are never so simple. After reading a study after study, it has become painfully clear to me, that while the results they sport may be indeed true, their application is limited in the process of actual language acquisition.

Oh, and by the way, getting rid of the funny accents was a joke. To understand some of the critique you should be aware that in the field of SLA, some scholars distinguish between learning and language acquisition. Most of the studies that recognise the distinction, however, are done in the fields of morphology and syntax. Some recent evidence supporting that speech learning is optimally learned by implicit neural systems exists, however: Chandrasekaran et al. So, here goes my list of questions we should be asking:.


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For example: Chinese tones form a phonemic category for Chinese speakers both L1 and sufficiently advanced L2 ; they are used to distinguish between meanings of words which may be otherwise similar. That means that Chinese speakers are not only able to distinguish aural stimuli based on these categories, but they are also able to retain words that are distinguished by these categories in their mental lexicon, and they are able to use these words to communicate meaning without much of a thought.

As said above, native speakers, for sure, have heightened sensitivity of the perceptual space at category border. There is evidence Heeren that although phonetic not meaning-based short-term high variability training helps to form categories of sound identification, the trainees fail to develop sensitivity peaks at category borders — however, advanced second language learners three years of majoring in the second language in college do develop sensitivity peaks at category borders.

This begs the question: is a heightened sensitivity at the category border a sign of an acquired phonemic category? Elman showed that the simple recurrent network SRN can learn the hierarchical recursive structure of sentences. As we think ahead we also must develop SOM models of language that can make distinct predictions in light of the simulations and empirical data.

In some cases, the empirical data may have not yet been obtained, or cannot be obtained e. Not only should computational modeling verify existing patterns of behavior on another platform, it should also inform theories of L1 and L2 acquisition by making distinct predictions under different hypotheses or conditions. In so doing, computational modeling will provide a new forum for generating novel ideas, inspiring new experiments, and helping formulate new theories see McClelland, for a discussion of the role of modeling in cognitive science. Finally, computationally minded researchers in language science should follow a recent call by Addyman and French to make an effort to provide user-friendly interfaces and tools to non-modelers, so that many more students of language acquisition can test computational models without fearing the technical hurdles posed by programming languages, source codes, and simulating environments.

[Phonology] How to Solve a Phonology Problem

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Addyman, C. Computational modeling in cognitive science: a manifesto for change. Basnight-Brown, D. Differences in semantic and translation priming across languages: the role of language direction and language dominance. Bates, E.

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Broman and J. New directions in research on language development. Benedict, H. Early lexical development: comprehension and production. Child Lang. Bickerton, D. The language bioprogram hypothesis. Brain Sci. Bloom, K. Semantics of verbs and the development of verb inflection in child language. Language 56, — Bowers, J. Challenging the widespread assumption that connectionism and distributed representations go hand-in-hand. Clark, E.

Input-based Phonological Acquisition (Outstanding Dissertations in Linguistics)

First Language Acquisition , 2nd Edn. Cambridge: Cambridge University Press. Comprehension, production, and language acquisition. Cuppini, C. Learning the lexical aspects of a second language at different proficiencies: a neural computational study. Dale, P. Lexical development norms for young children.


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