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On drawing a line through the spectrogram: how do we understand deficits of vocal pitch imitation?

Overview of attention for article published in Frontiers in Human Neuroscience, May 2015
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Title
On drawing a line through the spectrogram: how do we understand deficits of vocal pitch imitation?
Published in
Frontiers in Human Neuroscience, May 2015
DOI 10.3389/fnhum.2015.00271
Pubmed ID
Authors

Peter Q. Pfordresher, Pauline Larrouy-Maestri

Abstract

In recent years there has been a remarkable increase in research focusing on deficits of pitch production in singing. A critical concern has been the identification of "poor pitch singers," which we refer to more generally as individuals having a "vocal pitch imitation deficit." The present paper includes a critical assessment of the assumption that vocal pitch imitation abilities can be treated as a dichotomy. Though this practice may be useful for data analysis and may be necessary within educational practice, we argue that this approach is complicated by a series of problems. Moreover, we argue that a more informative (and less problematic) approach comes from analyzing vocal pitch imitation abilities on a continuum, referred to as effect magnitude regression, and offer examples concerning how researchers may analyze data using this approach. We also argue that the understanding of this deficit may be better served by focusing on the effects of experimental manipulations on different individuals, rather than attempt to treat values of individual measures, and isolated tasks, as absolute measures of ability.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
United States 1 3%
Denmark 1 3%
Canada 1 3%
Unknown 32 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 22%
Student > Ph. D. Student 6 17%
Student > Master 5 14%
Student > Bachelor 3 8%
Other 3 8%
Other 6 17%
Unknown 5 14%
Readers by discipline Count As %
Psychology 10 28%
Arts and Humanities 7 19%
Neuroscience 3 8%
Agricultural and Biological Sciences 2 6%
Computer Science 2 6%
Other 4 11%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 June 2015.
All research outputs
#18,416,517
of 22,813,792 outputs
Outputs from Frontiers in Human Neuroscience
#6,065
of 7,148 outputs
Outputs of similar age
#192,001
of 264,712 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#156
of 177 outputs
Altmetric has tracked 22,813,792 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
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