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1
Learning to Perceive Non-Native Tones via Distributional Training: Effects of Task and Acoustic Cue Weighting
In: Brain Sciences; Volume 12; Issue 5; Pages: 559 (2022)
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2
Perception and timing of acoustic distance
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3
Acoustic absement files
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4
The Perceptimatic English Benchmark for Speech Perception Models
In: CogSci 2020 - 42nd Annual Virtual Meeting of the Cognitive Science Society ; https://hal.archives-ouvertes.fr/hal-03087248 ; CogSci 2020 - 42nd Annual Virtual Meeting of the Cognitive Science Society, Jul 2020, Toronto / Virtual, Canada (2020)
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5
How do words compete? Quantifying lexical competition with acoustic distance
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6
Lexical ambiguity and acoustic distance in discrimination
In: Proceedings of the Linguistic Society of America; Vol 5, No 1 (2020): Proceedings of the Linguistic Society of America; 431–445 ; 2473-8689 (2020)
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7
Using acoustic distance to quantify lexical competition
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8
How acoustic distinctiveness affects spoken word recognition: A pilot study
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9
Software for objective comparison of vocal acoustic features over weeks of audio recording: KLFromRecordingDays
Abstract: KLFromRecordingDays allows measurement of Kullback–Leibler (KL) distances between 2D probability distributions of vocal acoustic features. Greater KL distance measures reflect increased phonological divergence across the vocalizations compared. The software has been used to compare *.wav file recordings made by Sound Analysis Recorder 2011 of songbird vocalizations pre- and post-drug and surgical manipulations. Recordings from individual animals in *.wav format are first organized into subdirectories by recording day and then segmented into individual syllables uttered and acoustic features of these syllables using Sound Analysis Pro 2011 (SAP). KLFromRecordingDays uses syllable acoustic feature data output by SAP to a MySQL table to generate and compare “template� (typically pre-treatment) and “target� (typically post-treatment) probability distributions. These distributions are a series of virtual 2D plots of the duration of each syllable (as x -axis) to each of 13 other acoustic features measured by SAP for that syllable (as y -axes). Differences between “template� and “target� probability distributions for each acoustic feature are determined by calculating KL distance, a measure of divergence of the target 2D distribution pattern from that of the template. KL distances and the mean KL distance across all acoustic features are calculated for each recording day and output to an Excel spreadsheet. Resulting data for individual subjects may then be pooled across treatment groups and graphically summarized and used for statistical comparisons. Because SAP-generated MySQL files are accessed directly, data limits associated with spreadsheet output are avoided, and the totality of vocal output over weeks may be objectively analyzed all at once. The software has been useful for measuring drug effects on songbird vocalizations and assessing recovery from damage to regions of vocal motor cortex. It may be useful in studies employing other species, and as part of speech therapies tracking progress in producing distinct speech sounds in isolation. ; Open Access Fund
Keyword: Acoustic analysis; Kullback–Leibler Distance; Phonology; Vocal learning
URL: http://hdl.handle.net/10342/7105
https://doi.org/10.1016/j.softx.2017.10.003
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10
Auditory Perception in an Open Space: Detection and Recognition
In: DTIC (2015)
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11
Intelligibility of foreign-accented words: Acoustic distances and gradient foreign accentedness
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12
Intelligibility of foreign-accented words: Acoustic distances and gradient foreign accentedness
Porretta, Vincent; Tucker, Benjamin V.. - : University of Alberta, 2015
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13
Transmission Characteristics of Solo Songs and Duets in a Neotropical Thicket Habitat Specialist Bird
In: Biological Sciences Publications (2015)
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14
Afrikaans and Dutch as closely-related languages: A comparison to West Germanic languages and Dutch dialects
In: Stellenbosch Papers in Linguistics Plus, Vol 47, Iss 0, Pp 1-18 (2015) (2015)
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15
Proposals for a representation of sounds based on their main acoustic-perceptual properties, Tones and Features
In: Tones and Features, Phonetic and Phonological Perspectives ; https://halshs.archives-ouvertes.fr/halshs-00675777 ; Ed. by Goldsmith, John A. Hume, Elizabeth and Wetzels, Leo. Tones and Features, Phonetic and Phonological Perspectives, Mouton de Gruyter, pp.306-330, 2011, Series: Studies in Generative Grammar [SGG] 107 (2011)
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16
The Synergy between Bounded-Distance HMM and Spectral Subtraction for Robust Speech Recognition
: Elsevier, 2011
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17
Implementation and Evaluation of Acoustic Distance Measures for Syllables
Munier, Christian. - : Bielefeld University, 2011
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18
The synergy between bounded-distance HMM and spectral subtraction for robust speech recognition
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19
The Synergy between Bounded-Distance HMM and Spectral Subtraction for Robust Speech Recognition
In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.archives-ouvertes.fr/hal-00592583 ; Speech Communication, Elsevier : North-Holland, 2009, 52 (2), pp.123. ⟨10.1016/j.specom.2009.09.002⟩ (2009)
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20
Sound Basics: A Primer in Psychoacoustics
In: DTIC AND NTIS (1998)
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