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1
Unsupervised Acoustic Unit Discovery by Leveraging a Language-Independent Subword Discriminative Feature Representation ...
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The effect of intermittent noise on lexically-guided perceptual learning in native and non-native listening
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3
The Effects of Onset and Offset Masking on the Time Course of Non-Native Spoken-Word Recognition in Noise ...
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4
The Effects of Onset and Offset Masking on the Time Course of Non-Native Spoken-Word Recognition in Noise ...
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5
Speech technology for unwritten languages
In: ISSN: 2329-9290 ; EISSN: 2329-9304 ; IEEE/ACM Transactions on Audio, Speech and Language Processing ; https://hal.inria.fr/hal-02480675 ; IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2020, ⟨10.1109/TASLP.2020.2973896⟩ (2020)
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6
How Phonotactics Affect Multilingual and Zero-shot ASR Performance ...
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7
That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages ...
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8
Cross-linguistic Influences on Sentence Accent Detection in Background Noise. ...
Scharenborg, Odette; Kakouros, Sofoklis; Post, Brechtje. - : Apollo - University of Cambridge Repository, 2020
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9
Cross-linguistic Influences on Sentence Accent Detection in Background Noise.
Scharenborg, Odette; Kakouros, Sofoklis; Post, Brechtje. - : SAGE Publications, 2020. : Lang Speech, 2020
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10
Talker-familiarity benefit in non-native recognition memory and word identification: The role of listening conditions and proficiency [<Journal>]
Drozdova, Polina [Verfasser]; Hout, Roeland van [Verfasser]; Scharenborg, Odette [Verfasser]
DNB Subject Category Language
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11
Cross-linguistic Influences on Sentence Accent Detection in Background Noise
In: ISSN: 0023-8309 ; Language and Speech ; https://hal.archives-ouvertes.fr/hal-02433650 ; Language and Speech, SAGE Publications (UK and US), 2019, pp.002383091881957. &#x27E8;10.1177/0023830918819573&#x27E9; (2019)
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12
Cross-linguistic Influences on Sentence Accent Detection in Background Noise
Abstract: This paper investigates whether sentence accent detection in a non-native language is dependent on (relative) similarity between prosodic cues to accent between the non-native and the native language, and whether cross-linguistic differences in the use of local and more widely distributed (i.e., non-local) cues to sentence accent detection lead to differential effects of the presence of background noise on sentence accent detection in a non-native language. We compared Dutch, Finnish, and French non-native listeners of English, whose cueing and use of prosodic prominence is gradually further removed from English, and compared their results on a phoneme monitoring task in different levels of noise and a quiet condition to those of native listeners. Overall phoneme detection performance was high for the native and the non-native listeners, but deteriorated to the same extent in the presence of background noise. Crucially, relative similarity between the prosodic cues to sentence accent of one’s native language compared to that of a non-native language does not determine the ability to perceive and use sentence accent for speech perception in that non-native language. Moreover, proficiency in the non-native language is not a straightforward predictor of sentence accent perception performance, although high proficiency in a non-native language can seemingly overcome certain differences at the prosodic level between the native and non-native language. Instead, performance is determined by the extent to which listeners rely on local cues (English and Dutch) versus cues that are more distributed (Finnish and French), as more distributed cues survive the presence of background noise better.
Keyword: Articles
URL: https://doi.org/10.1177/0023830918819573
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7066482/
http://www.ncbi.nlm.nih.gov/pubmed/30606083
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13
Sentence Accent Perception in Noise by French Non-Native Listeners of English
In: 9th International Conference on Speech Prosody 2018 ; https://hal.archives-ouvertes.fr/hal-01860566 ; 9th International Conference on Speech Prosody 2018, Jun 2018, Poznań, Poland. &#x27E8;10.21437/SpeechProsody.2018-12&#x27E9; (2018)
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14
Bayesian models for unit discovery on a very low resource language
In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01709589 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2018, Calgary, Alberta, Canada (2018)
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15
Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop
In: ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01709578 ; ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Alberta, Canada (2018)
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16
Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop ...
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17
Speech perception by humans and machines
In: Speech perception and spoken word recognition (London, 2017), p. 181-204
MPI für Psycholinguistik
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18
Fine-Tracker
Scharenborg, Odette. - : Centre for Language and Speech Technology, Radboud University, 2014
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19
Phonological abstraction without phonemes in speech perception
In: Cognition. - Amsterdam [u.a] : Elsevier 129 (2013) 2, 356-361
OLC Linguistik
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20
Acoustic reduction in conversational Dutch: a quantitative analysis based on automatically generated segmental transcriptions
In: Journal of phonetics. - Amsterdam : Elsevier 39 (2011) 1, 96-109
BLLDB
OLC Linguistik
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