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—The importance of automatically recognizing emotions from human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications. This paper explores the detection of domain-specific emotions using language and discourse information in conjunction with acoustic correlates of emotion in speech signals. The(More)
—The paper considers the task of recognizing environmental sounds for the understanding of a scene or context surrounding an audio sensor. A variety of features have been proposed for audio recognition, including the popular Mel-frequency cepstral coefficients (MFCCs) which describe the audio spectral shape. Environmental sounds, such as chirpings of(More)
Speech Database (the " VAM Corpus "). It has been released by the HUMAINE Association under specific conditions for sole scientific, non-commercial use. In the following, the term " the corpus providers " includes all mentioned parties: the data providers, the University of Karlsruhe (TH), and the HUMAINE Association. Conditions of release. • The VAM Corpus(More)
Most paralinguistic analysis tasks are lacking agreed-upon evaluation procedures and comparability, in contrast to more 'traditional' disciplines in speech analysis. The INTERSPEECH 2010 Paralinguistic Challenge shall help overcome the usually low compatibility of results, by addressing three selected sub-challenges. In the Age Sub-Challenge, the age of(More)
With the advent of prosody annotation standards such as tones and break indices (ToBI), speech technologists and linguists alike have been interested in automatically detecting prosodic events in speech. This is because the prosodic tier provides an additional layer of information over the short-term segment-level features and lexical representation of an(More)
The interaction between human beings and computers will be more natural if computers are able to perceive and respond to human non-verbal communication such as emotions. Although several approaches have been proposed to recognize human emotions based on facial expressions or speech, relatively limited work has been done to fuse these two, and other,(More)
—During expressive speech, the voice is enriched to convey not only the intended semantic message but also the emotional state of the speaker. The pitch contour is one of the important properties of speech that is affected by this emotional modulation. Although pitch features have been commonly used to recognize emotions, it is not clear what aspects of the(More)
— Human emotional and cognitive states evolve with variable intensity and clarity through the course of social interactions and experiences, and they are continuously influenced by a variety of input multimodal information from the environment and the interaction participants. This has motivated the development of a new area within affective computing that(More)
Prosody is an important cue for identifying dialog acts. In this paper, we show that modeling the sequence of acoustic– prosodic values as n-gram features with a maximum entropy model for dialog act (DA) tagging can perform better than conventional approaches that use coarse representation of the prosodic contour through summative statistics of the(More)
In this paper, we describe a maximum entropy-based automatic prosody labeling framework that exploits both language and speech information. We apply the proposed framework to both prominence and phrase structure detection within the Tones and Break Indices (ToBI) annotation scheme. Our framework utilizes novel syntactic features in the form of supertags and(More)