The cycle revisited – the multiple application of phonological rules

2018 ◽  
pp. 84-130
Author(s):  
Jolanta Szpyra-Kozłowska
2016 ◽  
Vol 28 (1) ◽  
pp. 20-40 ◽  
Author(s):  
Velia Cardin ◽  
Eleni Orfanidou ◽  
Lena Kästner ◽  
Jerker Rönnberg ◽  
Bencie Woll ◽  
...  

The study of signed languages allows the dissociation of sensorimotor and cognitive neural components of the language signal. Here we investigated the neurocognitive processes underlying the monitoring of two phonological parameters of sign languages: handshape and location. Our goal was to determine if brain regions processing sensorimotor characteristics of different phonological parameters of sign languages were also involved in phonological processing, with their activity being modulated by the linguistic content of manual actions. We conducted an fMRI experiment using manual actions varying in phonological structure and semantics: (1) signs of a familiar sign language (British Sign Language), (2) signs of an unfamiliar sign language (Swedish Sign Language), and (3) invented nonsigns that violate the phonological rules of British Sign Language and Swedish Sign Language or consist of nonoccurring combinations of phonological parameters. Three groups of participants were tested: deaf native signers, deaf nonsigners, and hearing nonsigners. Results show that the linguistic processing of different phonological parameters of sign language is independent of the sensorimotor characteristics of the language signal. Handshape and location were processed by different perceptual and task-related brain networks but recruited the same language areas. The semantic content of the stimuli did not influence this process, but phonological structure did, with nonsigns being associated with longer RTs and stronger activations in an action observation network in all participants and in the supramarginal gyrus exclusively in deaf signers. These results suggest higher processing demands for stimuli that contravene the phonological rules of a signed language, independently of previous knowledge of signed languages. We suggest that the phonological characteristics of a language may arise as a consequence of more efficient neural processing for its perception and production.


Author(s):  
Min Li ◽  
Javed Absar ◽  
Bruno Bougard ◽  
Liesbet van der Perre ◽  
Francky Catthoor

1978 ◽  
Vol 5 (1) ◽  
pp. 101-112 ◽  
Author(s):  
John H. V. Gilbert ◽  
Carolyn E. Johnson

ABSTRACTThis paper reports the results of a preliminary study dealing with the ways in which children between six and seven years of age organize spoken language. In particular it deals with aspects of the temporal and segmental structure of polysyllabic English words containing the syllable C/jul/ (e.g. pediculous). On the basis of data presented, it is suggested (a) that in order to meet certain phonological conditions it is the relations between syllable (and not segment) durations which must undergo modification towards the adult duration values, and (b) that the achievement of such values is accompanied by some quasi-systematic alterations in phonological rules.


2019 ◽  
Vol 7 (2) ◽  
pp. 79-91
Author(s):  
Philippe Martin

An automated process for building a prosodic structure form transcribed speech recordings in French is presented, based on the incremental prosodic model [1, 2, 3]. In this model, the prosodic structure is defined incrementally by dependency relations instantiated by melodic contours located on the last syllable of the last word of stress groups, subject to a rhythmic constrain limiting the gap between successive stressed syllable to a 250-1250 ms range. Although they frequently contain lexical words (noun, verb, adverb, adjective), stress groups in French can also include only grammatical words (pronoun, conjunction, preposition). Melodic contours are phonologically defined from their melodic rise or fall and their glissando value ensuring their function as dependency markers between stress groups. The algorithm proceeds from an orthographic transcription as follows: 1. Automatic segmentation of the orthographic text into IPA and word tiers 2. Automatic annotation of stressed vowels in three classes (followed by 250 ms silence, above the glissando threshold and lexical category based) 3. Assignment of melodic contours from fundamental frequency values at stressed vowels boundaries. Comparisons with automatic and manual stressed syllable annotation on existing corpora are given, showing the validity of the phonological rules implemented in the algorithm.


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