An Eye-tracking Study of Transposed-letter Effect in English Word Recognition by Mandarin Speakers

2021 ◽  
Author(s):  
Huan LEI ◽  
Jianwu DANG ◽  
Yu CHEN
Keyword(s):  
Word Recognition ◽  
Eye Tracking ◽  
English Word ◽  
Mandarin Speakers ◽  
Transposed Letter Effect

Effects of native language on the use of segmental and suprasegmental cues to stress in English word recognition: An eye-tracking study

2016 ◽  
Vol 140 (4) ◽  
pp. 3336-3336
Author(s):  
Katrina Connell ◽  
Simone Hüls ◽  
Maria Teresa Martínez-García ◽  
Zhen Qin ◽  
Seulgi Shin ◽  
...  
Keyword(s):  
Word Recognition ◽  
Eye Tracking ◽  
Native Language ◽  
English Word ◽  
Suprasegmental Cues

Classroom Noise and Children Learning Through a Second Language

2005 ◽  
Vol 36 (3) ◽  
pp. 219-229 ◽  
Author(s):  
Peggy Nelson ◽  
Kathryn Kohnert ◽  
Sabina Sabur ◽  
Daniel Shaw
Keyword(s):  
Second Language ◽  
Word Recognition ◽  
Signal To Noise Ratio ◽  
Recognition Performance ◽  
Recognition Task ◽  
English Word ◽  
Noise Condition ◽  
English Only ◽  
Task Behavior ◽  
The Impact

Purpose: Two studies were conducted to investigate the effects of classroom noise on attention and speech perception in native Spanish-speaking second graders learning English as their second language (L2) as compared to English-only-speaking (EO) peers. Method: Study 1 measured children’s on-task behavior during instructional activities with and without soundfield amplification. Study 2 measured the effects of noise (+10 dB signal-to-noise ratio) using an experimental English word recognition task. Results: Findings from Study 1 revealed no significant condition (pre/postamplification) or group differences in observations in on-task performance. Main findings from Study 2 were that word recognition performance declined significantly for both L2 and EO groups in the noise condition; however, the impact was disproportionately greater for the L2 group. Clinical Implications: Children learning in their L2 appear to be at a distinct disadvantage when listening in rooms with typical noise and reverberation. Speech-language pathologists and audiologists should collaborate to inform teachers, help reduce classroom noise, increase signal levels, and improve access to spoken language for L2 learners.

Visual Word Recognition in Multilinguals

2018 ◽  
pp. 117-143
Author(s):  
Ton Dijkstra ◽  
Walter J. B. van Heuven
Keyword(s):  
Pattern Recognition ◽  
Reaction Time ◽  
Word Recognition ◽  
Eye Tracking ◽  
Sentence Context ◽  
Event Related Potential ◽  
Word Retrieval ◽  
Context Sensitive ◽  
Temporal Properties ◽  
Interlingual Homographs

This chapter on the reading of words by multilinguals considers how retrieving words in two or more languages is affected by the lexical properties of the words, the sentence context in which they occur, and the language to which they belong. Reaction time and event-related potential (ERP) studies are discussed that investigate the processing of cognates, interlingual homographs, and words with different numbers of neighbors, both in isolation and in sentence context. After reviewing different models for multilingual word retrieval, it is concluded that multilingual word recognition involves a language-independent, context-sensitive, and interactive pattern recognition routine, with temporal properties that can be determined not only by “classical” reaction time techniques, but even better by up-to-date research techniques such as eye-tracking and ERP recordings.

scholarly journals Recognition times for 62 thousand English words: Data from the English Crowdsourcing Project

2019 ◽  
Author(s):  
Marc Brysbaert ◽  
Emmanuel Keuleers ◽  
Paweł Mandera
Keyword(s):  
Word Recognition ◽  
Response Times ◽  
Native English Speakers ◽  
English Word ◽  
English Speakers ◽  
Vocabulary Test ◽  
Response Latencies ◽  
Virtual Experiments

We present a new dataset of English word recognition times for a total of 62 thousand words, called the English Crowdsourcing Project. The data were collected via an internet vocabulary test, in which more than one million people participated. The present dataset is limited to native English speakers. Participants were asked to indicate which words they knew. Their response times were registered, although at no point were the participants asked to respond as fast as possible. Still, the response times correlate around .75 with the response times of the English Lexicon Project for the shared words. Also results of virtual experiments indicate that the new response times are a valid addition to the English Lexicon Project. This not only means that we have useful response times for some 35 thousand extra words, but we now also have data on differences in response latencies as a functionof education and age.

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