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Engagement in the Use of English and Chinese as Foreign Languages: The Role of Learner-Generated Content in Instructional Task Design
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Medium of instruction ideologies: accommodation of multilingualism in the bilingual regime of Navarre
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In: Erdocia, Iker orcid:0000-0003-2459-1346 (2019) Medium of instruction ideologies: accommodation of multilingualism in the bilingual regime of Navarre. Current Issues in Language Planning, 20 (3). pp. 284-308. ISSN 1466-4208 (2019)
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Effects of Implicit and Explicit Focus on Form on L2 Acquisition of the English Passive
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Investigating the Construct of Topical Knowledge in a Scenario-Based Assessment Designed to Simulate Real-Life Second Language Use
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Complexity Theory and Language Development: In celebration of Diane Larsen-Freeman
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An exploratory study of foreign accent and phonological awareness in Korean learners of English
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| 7 |
Word-external properties in a typology of Modern English: A comparison with German
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In: English Language and Linguistics, vol 23, iss 3 (2019)
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| 8 |
Heritage speakers' use of prosodic strategies in focus marking in Spanish
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In: INTERNATIONAL JOURNAL OF BILINGUALISM, vol 23, iss 5 (2019)
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| 9 |
Spelling errors in english derivational suffixes reflect morphological boundary strength: A case study
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In: Mental Lexicon, vol 14, iss 1 (2019)
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| 10 |
Towards Understanding Voice Discrimination Abilities of Humans and Machines
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In: Park, Soo Jin. (2019). Towards Understanding Voice Discrimination Abilities of Humans and Machines. UCLA: Electrical and Computer Engineering 0333. Retrieved from: http://www.escholarship.org/uc/item/22d942x3 (2019)
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Abstract:
An individual's voice can vary dramatically depending on word choice, affect, and other factors. Such intrinsic within-talker variability causes considerable difficulties when distinguishing talkers by their voices, both for humans and machines. For machines, phonetic content variability substantially degrades performance when utterances are short (e.g., < 10 sec). Humans, on the contrary, are less influenced by content variability, and they perform better than machines in such conditions. Hence, understanding which and how acoustic features are related to human responses might provide insights to improve machine performance. Yet, little is known about human and machine voice discrimination ability under various kinds of intrinsic within-talker variabilities.This dissertation presents studies of voice discrimination abilities of humans and machines under text, affect, and speaking-style variabilities. The main focus is in developing a feature set, based on a psychoacoustic model of voice quality, that can be used to improve machine performance and to find acoustic correlates with human responses. In order to systematically investigate the effects of within- and between-talker variability, a database was developed at UCLA. More than a hundred females and a hundred males were recorded with various speech styles, including sustained vowels, read sentences, affective speech, and pet-directed speech.Preliminary experiments indicated that the voice quality feature set (VQual1) was promising for predicting human responses, and for improving automatic speaker verification (ASV) performance which degraded significantly under text, affect and/or speaking-style variabilities. VQual1 was modified to another set (VQual2) to better differentiate talkers, leading to further improvements in short-utterance text-independent ASV tasks. Voice discrimination abilities of humans and machines for very short utterances (~ 2 sec) under high text and style variability were analyzed using read sentences and pet-directed speech. Humans were more accurate than machines for read sentence pairs, but the performance difference became small for style-mismatched pairs and for perceptually marked talkers. Humans' and machines' decision spaces were weakly correlated, indicating a weak or non-linear relationship between talker representations by humans and machines. However, for different-talker pairs, the VQual2-based system responses were highly correlated with human responses. Results also suggested that machines could supplement human decisions for perceptually marked talkers. Additionally, VQual2 was effective in perceived affect recognition, suggesting another application where voice quality features can contribute to predict human decisions.
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Keyword:
Automatic speaker recognition; Engineering; Linguistics; Psychology; Speaker perception; Voice discrimination; Voice quality
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URL: http://www.escholarship.org/uc/item/22d942x3
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| 11 |
“Our Beautiful Family”: A study of English Language Learners’ dual language identity texts and linguistic identity in a family literacy program ...
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The Effectiveness of Corpus-Aided Instruction Using Lexical Bundles to Improve Academic Writing in Instructed Second Language Acquisition: A Multimethod Research Design
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In: http://rave.ohiolink.edu/etdc/view?acc_num=osu1556003595087828 (2019)
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| 14 |
Strategies ESL Saudi Arabian Graduate Students Use to Learn New Academic Vocabulary Across Domains
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In: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1554976746592993 (2019)
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| 15 |
The Policy and Politics of Second Language Teaching
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In: http://rave.ohiolink.edu/etdc/view?acc_num=ouashonors1556284044333655 (2019)
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| 16 |
Can kiwis and koalas as cultural primes induce perceptual bias in Australian English speaking listeners?
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In: Laboratory Phonology: Journal of the Association for Laboratory Phonology; Vol 10, No 1 (2019); 7 ; 1868-6354 (2019)
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| 17 |
A Formal Syntactic Analysis of Complex-Path Motion Predicates in Ghanaian Student Pidgin (GSP) ...
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A Formal Syntactic Analysis of Complex-Path Motion Predicates in Ghanaian Student Pidgin (GSP) ...
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| 19 |
Language change and grammar teaching books in EFL
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In: Journal of Contemporary Education, Theory & Research 3 (2019) 1, S. 15-20 (2019)
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| 20 |
Proverb Database: Corpus of American English Proverbs (CAEP) and Experimental Study
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