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Using ultrasound tongue imaging to identify covert contrasts in children’s speech

Overview of attention for article published in Clinical Linguistics & Phonetics, June 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)

Mentioned by

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4 tweeters

Citations

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15 Dimensions

Readers on

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25 Mendeley
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Title
Using ultrasound tongue imaging to identify covert contrasts in children’s speech
Published in
Clinical Linguistics & Phonetics, June 2016
DOI 10.1080/02699206.2016.1180713
Pubmed ID
Authors

Natalia Zharkova, Fiona E. Gibbon, Alice Lee

Abstract

Ultrasound tongue imaging has become a promising technique for detecting covert contrasts, due to the developments in data analysis methods that allow for processing information on tongue shape from young children. An important feature concerning analyses of ultrasound data from children who are likely to produce covert contrasts is that the data are likely to be collected without head-to-transducer stabilisation, due to the speakers' age. This article is a review of the existing methods applicable in analysing data from non-stabilised recordings. The article describes some of the challenges of ultrasound data collection from children, and analysing these data, as well as possible ways to address those challenges. Additionally, there are examples from typical and disordered productions featuring covert contrasts, with illustrations of quantifying differences in tongue shape between target speech sounds.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 20%
Student > Ph. D. Student 4 16%
Student > Doctoral Student 3 12%
Student > Postgraduate 2 8%
Lecturer 1 4%
Other 4 16%
Unknown 6 24%
Readers by discipline Count As %
Nursing and Health Professions 7 28%
Medicine and Dentistry 6 24%
Linguistics 4 16%
Social Sciences 2 8%
Psychology 1 4%
Other 0 0%
Unknown 5 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 June 2016.
All research outputs
#3,061,941
of 7,942,916 outputs
Outputs from Clinical Linguistics & Phonetics
#85
of 263 outputs
Outputs of similar age
#88,053
of 262,868 outputs
Outputs of similar age from Clinical Linguistics & Phonetics
#6
of 8 outputs
Altmetric has tracked 7,942,916 research outputs across all sources so far. This one has received more attention than most of these and is in the 61st percentile.
So far Altmetric has tracked 263 research outputs from this source. They receive a mean Attention Score of 2.3. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 262,868 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.