license:cc-by-4.0 region:us
ASVP-ESD
@article{gsj2020asvpesd,
  title={ASVP-ESD:A dataset and its benchmark for emotion recognition using both speech and non-speech utterances},
  author={Dejoli Tientcheu Touko Landry and Qianhua He and Haikang Yan and Yanxiong Li},
  journal={Global Scientific Journals},
  volume={8},
  issue={6},
  pages={1793--1798},
  year={2020}
}
---
license: cc-by-4.0
---

# The Audio, Speech, and Vision Processing Lab - Emotional Sound Database (ASVP - ESD)

## ABOUT

The Audio, Speech, and Vision Processing Lab - Emotional Sound Database (ASVP - ESD) 
was created by School of Electronic and Information Engineering, South China University of Technology.

## CHOSEN EMOTIONS

13 emotions were chosen:
1. boredom,sigh
2. neutral,calm
3. happy,laugh,gaggle
4. sad,cry
5. angry,grunt,frustration
6. fearful,scream,panic
7. disgust,dislike,contempt
8. surprised,gasp,amazed
9. excited
10. pleasure
11. pain,groan
12. disappointment,disapproval
13. breath

## ORGANISING THE DATABASE

### Speech Statistic

| Duration Statisitc         | Duration                                          |
| -------------------------- |:-------------------------------------------------:|
| Num. of Clips              | 2,150                                             |
| Total Duration             | 13347.835 seconds = 222.464 minutes = 3.708 hours |
| Max Dur                    | 32.235 seconds                                    |
| Min Dur                    | 0.287 seconds                                     |
| Mean Dur                   | 6.208 seconds                                     |
| Std. Dur                   | 3.839 seconds                                     |
| Num. of Clips > 30 seconds | 1                                                 |

| Emotion                         | Num. of Clips |
| ------------------------------- |:-------------:|
| 01: boredom, sigh               | 81            |
| 02: neutral, calm               | 657           |
| 03: happy, laugh, gaggle        | 154           |
| 04: sad, cry                    | 268           |
| 05: angry, grunt, frustration   | 385           |
| 06: fearful, scream, panic      | 63            |
| 07: disgust, dislike, contempt  | 90            |
| 08: surprised, hasp, amazed     | 144           |
| 09: excited                     | 136           |
| 10: pleasure                    | 15            |
| 11: pain, groan                 | 25            |
| 12: disappointmrnt, disapproval | 132           |
| 13: breath                      | 0             |

| Emotion Intensity | Num. of Clips |
| ----------------- |:-------------:|
|  01: normal       | 1,783         |
|  02: high         | 367           |

| Gender      | Num. of Clips |
| ----------- |:-------------:|
|  01: male   | 1,224         |
|  02: female | 926           |

| Age Range  | Num. of Clips |
| ---------- |:-------------:|
|  01: >65   | 65            |
|  02: 20~65 | 1,914         |
|  03: 3<20  | 80            |
|  04: <3    | 91            |

| Language      | Num. of Clips |
| ------------- |:-------------:|
|  01: Mandarin | 937           |
|  02: English  | 621           |
|  03: French   | 175           |
|  04: Others   | 417           |

### Non-Speech Statistic

| Duration Statisitc         | Duration                                          |
| -------------------------- |:-------------------------------------------------:|
| Num. of Clips              | 5,484                                             |
| Total Duration             | 14438.117 seconds = 240.635 minutes = 4.011 hours |
| Max Dur                    | 25.810 seconds                                    |
| Min Dur                    | 0.141 seconds                                     |
| Mean Dur                   | 2.633 seconds                                     |
| Std. Dur                   | 2.720 seconds                                     |
| Num. of Clips > 30 seconds | 0                                                 |

| Emotion                         | Num. of Clips |
| ------------------------------- |:-------------:|
| 01: boredom, sigh               | 392           |
| 02: neutral, calm               | 253           |
| 03: happy, laugh, gaggle        | 878           |
| 04: sad, cry                    | 383           |
| 05: angry, grunt, frustration   | 339           |
| 06: fearful, scream, panic      | 799           |
| 07: disgust, dislike, contempt  | 473           |
| 08: surprised, hasp, amazed     | 808           |
| 09: excited                     | 109           |
| 10: pleasure                    | 273           |
| 11: pain, groan                 | 706           |
| 12: disappointmrnt, disapproval | 70            |
| 13: breath                      | 1             |

| Emotion Intensity | Num. of Clips |
| ----------------- |:-------------:|
|  01: normal       | 4,693         |
|  02: high         | 791           |

| Gender      | Num. of Clips |
| ----------- |:-------------:|
|  01: male   | 2,919         |
|  02: female | 2,565         |

| Age Range  | Num. of Clips |
| ---------- |:-------------:|
|  01: >65   | 73            |
|  02: 20~65 | 5,224         |
|  03: 3<20  | 100           |
|  04: <3    | 87            |

| Language      | Num. of Clips |
| ------------- |:-------------:|
|  01: Mandarin | 512           |
|  02: English  | 3,258         |
|  03: French   | 109           |
|  04: Others   | 1,605         |

## References

1. Dejoli Tientcheu Touko Landry, Qianhua He, Haikang Yan and Yanxiong Li. (2020). ASVP-ESD:A dataset and its benchmark for emotion recognition using both speech and non-speech utterances. Global Scientific Journals, 8(6), 1793-1798.
 