In Search of Primary Rubrics for Language Independent Emotional Speech Identification

In this paper we describe recent work oriented towards establishing some background to support the design of successful "universal" (language independent, specifically) emotional speech identification systems. Our final goal is using such systems to improve state of the art advanced spoken language systems. We carried out several experiments with emotional speech databases for Spanish (SES) and German (EMODB), including language-dependent tasks (to establish the accuracy of the identification systems), and language independent (cross-language) tasks. We show how automatic emotion identification results can be comparable to those obtained by human listeners, provided that enough training data is available. Moreover, and in spite of data availability, we also show how there are emotions (sadness and anger) that are clearly identified in the automatic experiments, for both languages, showing a reasonably clear "language-independent" behavior of such emotions. Finally, we show how psychological considerations related to the emotional speech generation process can be somehow related to our experimental results, suggesting that previously identifying such psychological features may greatly help the development of high quality "universal" emotional speech identification systems.