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Auflistung nach Schlagwort "Speech emotion recognition"

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  • Zeitschriftenartikel
    An Evaluation of Emotion Units and Feature Types for Real-Time Speech Emotion Recognition
    (KI - Künstliche Intelligenz: Vol. 25, No. 3, 2011) Vogt, Thurid; André, Elisabeth
    Emotion recognition from speech in real-time is an upcoming research topic and the consideration of real-time constraints concerns all aspects of the recognition system. We present here a comparison of units and feature types for speech emotion recognition. To our knowledge, a comprehensive comparison of many different units on several databases is still missing in the literature and we also discuss units with special emphasis on real-time processing, that is, we do not only consider accuracy but also speed and ease of calculation. For the feature types, we also use only features that can be extracted fully automatically in real-time and look at which types best characterise which emotion classes. Gained insights are used as validation of methodology for our online speech emotion recognition system EmoVoice.
  • Zeitschriftenartikel
    Auditive Emotion Recognition for Empathic AI-Assistants
    (KI - Künstliche Intelligenz: Vol. 38, No. 3, 2024) Duwenbeck, Roswitha; Kirchner, Elsa Andrea
    This paper briefly introduces the Project “AudEeKA”, whose aim is to use speech and other bio signals for emotion recognition to improve remote, but also direct, healthcare. This article takes a look at use cases, goals and challenges, of researching and implementing a possible solution. To gain additional insights, the main-goal of the project is divided into multiple sub-goals, namely speech emotion recognition, stress detection and classification and emotion detection from physiological signals. Also, similar projects are considered and project-specific requirements stemming from use-cases introduced. Possible pitfalls and difficulties are outlined, which are mostly associated with datasets. They also emerge out of the requirements, their accompanying restrictions and first analyses in the area of speech emotion recognition, which are shortly presented and discussed. At the same time, first approaches to solutions for every sub-goal, which include the use of continual learning, and finally a draft of the planned architecture for the envisioned system, is presented. This draft presents a possible solution for combining all sub-goals, while reaching the main goal of a multimodal emotion recognition system.