| Title |
Evaluation of the effectiveness and efficiency of state-of-the-art features and models for automatic speech recognition error detection
|
|---|---|
| Published in |
Journal of Big Data, January 2021
|
| DOI | 10.1186/s40537-020-00391-w |
| Authors |
Asmaa El Hannani, Rahhal Errattahi, Fatima Zahra Salmam, Thomas Hain, Hassan Ouahmane |
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 % |
|---|---|---|
| Researcher | 4 | 16% |
| Student > Ph. D. Student | 2 | 8% |
| Student > Master | 2 | 8% |
| Professor | 2 | 8% |
| Librarian | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 11 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 40% |
| Agricultural and Biological Sciences | 2 | 8% |
| Unspecified | 1 | 4% |
| Social Sciences | 1 | 4% |
| Materials Science | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 10 | 40% |