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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A neural speech decoding framework leveraging deep learning and speech synthesis
|
|---|---|
| Published in |
Nature Machine Intelligence, April 2024
|
| DOI | 10.1038/s42256-024-00824-8 |
| Authors |
Xupeng Chen, Ran Wang, Amirhossein Khalilian-Gourtani, Leyao Yu, Patricia Dugan, Daniel Friedman, Werner Doyle, Orrin Devinsky, Yao Wang, Adeen Flinker |
X Demographics
The data shown below were collected from the profiles of 463 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 69 | 15% |
| United Kingdom | 20 | 4% |
| Canada | 13 | 3% |
| France | 10 | 2% |
| India | 10 | 2% |
| Japan | 9 | 2% |
| Brazil | 6 | 1% |
| Germany | 3 | <1% |
| Nigeria | 3 | <1% |
| Other | 44 | 10% |
| Unknown | 276 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 403 | 87% |
| Scientists | 49 | 11% |
| Practitioners (doctors, other healthcare professionals) | 8 | 2% |
| Science communicators (journalists, bloggers, editors) | 3 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 6 | 32% |
| Student > Ph. D. Student | 5 | 26% |
| Student > Bachelor | 1 | 5% |
| Researcher | 1 | 5% |
| Student > Postgraduate | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 6 | 32% |
| Engineering | 5 | 26% |
| Computer Science | 2 | 11% |
| Social Sciences | 1 | 5% |
| Unknown | 5 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 384. 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 08 May 2024.
All research outputs
#82,708
of 25,941,588 outputs
Outputs from Nature Machine Intelligence
#21
of 788 outputs
Outputs of similar age
#983
of 301,485 outputs
Outputs of similar age from Nature Machine Intelligence
#3
of 37 outputs
Altmetric has tracked 25,941,588 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 788 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 67.6. This one has done particularly well, scoring higher than 97% 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 301,485 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.