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A hybrid input-type recurrent neural network for LVCSR language modeling

Overview of attention for article published in EURASIP Journal on Audio, Speech, and Music Processing, August 2016
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1 X user

Citations

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13 Mendeley
Title
A hybrid input-type recurrent neural network for LVCSR language modeling
Published in
EURASIP Journal on Audio, Speech, and Music Processing, August 2016
DOI 10.1186/s13636-016-0093-x
Authors

Vataya Chunwijitra, Ananlada Chotimongkol, Chai Wutiwiwatchai

X Demographics

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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 31%
Lecturer 2 15%
Student > Master 2 15%
Researcher 2 15%
Student > Bachelor 1 8%
Other 1 8%
Unknown 1 8%
Readers by discipline Count As %
Computer Science 10 77%
Mathematics 1 8%
Engineering 1 8%
Unknown 1 8%
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 12 August 2016.
All research outputs
#20,656,161
of 25,374,647 outputs
Outputs from EURASIP Journal on Audio, Speech, and Music Processing
#101
of 131 outputs
Outputs of similar age
#297,655
of 378,559 outputs
Outputs of similar age from EURASIP Journal on Audio, Speech, and Music Processing
#1
of 2 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% 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 10th percentile – i.e., 10% 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 378,559 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% 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. This one has scored higher than all of them