A Comparative Cross Language View On Acted Databases Portraying Basic Emotions Utilising Machine Learning (2022.lrec-1)
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| Challenge: | Since several decades emotional databases have been recorded by various laboratories. |
| Approach: | They propose to model similarity as performance in cross database machine learning experiments and to analyze a manually picked set of four acoustic features that represent different phonetic areas. |
| Outcome: | The proposed sets of features represent different phonetic areas and are comparable across languages. |
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