Emotion recognition in Arabic speech
| Autor: | Lama Hamandi, Ziad Osman, Rached Zantout, Samira Klaylat |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Arabic
02 engineering and technology computer.software_genre GeneralLiterature_MISCELLANEOUS German 030507 speech-language pathology & audiology 03 medical and health sciences 0202 electrical engineering electronic engineering information engineering Natural (music) Emotion recognition business.industry Speech corpus language.human_language Surfaces Coatings and Films ComputingMethodologies_PATTERNRECOGNITION Hardware and Architecture Signal Processing language Classification methods 020201 artificial intelligence & image processing Artificial intelligence 0305 other medical science Psychology business computer Natural language processing |
| Zdroj: | Analog Integrated Circuits and Signal Processing. 96:337-351 |
| ISSN: | 1573-1979 0925-1030 |
| DOI: | 10.1007/s10470-018-1142-4 |
| Popis: | Automatic emotion recognition from speech signals without linguistic cues has been an important emerging research area. Integrating emotions in human---computer interaction is of great importance to effectively simulate real life scenarios. Research has been focusing on recognizing emotions from acted speech while little work was done on natural real life utterances. English, French, German and Chinese corpora were used for that purpose while no natural Arabic corpus was found to date. In this paper, emotion recognition in Arabic spoken data is studied for the first time. A realistic speech corpus from Arabic TV shows is collected. The videos are labeled by their perceived emotions; namely happy, angry or surprised. Prosodic features are extracted and thirty-five classification methods are applied. Results are analyzed in this paper and conclusions and future recommendations are identified. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink