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A Decision-Tree-Based Algorithm for Speech/Music Classification and Segmentation

Overview of attention for article published in EURASIP Journal on Audio, Speech, and Music Processing, June 2009
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About this Attention Score

  • Among the highest-scoring outputs from this source (#34 of 131)

Mentioned by

patent
3 patents

Citations

dimensions_citation
58 Dimensions

Readers on

mendeley
54 Mendeley
Title
A Decision-Tree-Based Algorithm for Speech/Music Classification and Segmentation
Published in
EURASIP Journal on Audio, Speech, and Music Processing, June 2009
DOI 10.1155/2009/239892
Authors

Yizhar Lavner, Dima Ruinskiy

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 2%
France 1 2%
Unknown 52 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 22%
Student > Master 11 20%
Student > Bachelor 8 15%
Researcher 6 11%
Student > Postgraduate 2 4%
Other 3 6%
Unknown 12 22%
Readers by discipline Count As %
Computer Science 22 41%
Engineering 11 20%
Arts and Humanities 4 7%
Mathematics 1 2%
Business, Management and Accounting 1 2%
Other 3 6%
Unknown 12 22%
Attention Score in Context

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 03 May 2022.
All research outputs
#8,535,472
of 25,374,917 outputs
Outputs from EURASIP Journal on Audio, Speech, and Music Processing
#34
of 131 outputs
Outputs of similar age
#42,238
of 122,387 outputs
Outputs of similar age from EURASIP Journal on Audio, Speech, and Music Processing
#2
of 2 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 131 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 122,387 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.