The Automatic Recognition of Emotions in Speech

• Published in: Emotion-Oriented Systems pp. 71 - 99
• Main Authors: Batliner, Anton, Schuller, Björn, Seppi, Dino, Steidl, Stefan, Devillers, Laurence, Vidrascu, Laurence, Vogt, Thurid, Aharonson, Vered, Amir, Noam
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 01.01.2011
• Series: Cognitive Technologies
• Subjects: Acoustic Feature; Emotion Recognition; Independent Component Analysis; Linear Discriminant Analysis; Recognition Rate
• ISBN: 3642151833; 9783642151835
• ISSN: 1611-2482
• DOI: 10.1007/978-3-642-15184-2_6

In this chapter, we focus on the automatic recognition of emotional states using acoustic and linguistic parameters as features and classifiers as tools to predict the ‘correct’ emotional states. We first sketch history and state of the art in this field; then we describe the process of ‘corpus engineering’, i.e. the design and the recording of databases, the annotation of emotional states, and further processing such as manual or automatic segmentation. Next, we present an overview of acoustic and linguistic features that are extracted automatically or manually. In the section on classifiers, we deal with topics such as the curse of dimensionality and the sparse data problem, classifiers, and evaluation. At the end of each section, we point out important aspects that should be taken into account for the planning or the assessment of studies. The subject area of this chapter is not emotions in some narrow sense but in a wider sense encompassing emotion-related states such as moods, attitudes, or interpersonal stances as well. We do not aim at an in-depth treatise of some specific aspects or algorithms but at an overview of approaches and strategies that have been used or should be used.