Download Speaker Classification II: Selected Projects by Susanne Schötz, Christian Müller (auth.), Christian Müller PDF

By Susanne Schötz, Christian Müller (auth.), Christian Müller (eds.)

As good as conveying a message in phrases and sounds, the speech sign contains information regarding the speaker's personal anatomy, body structure, linguistic event and psychological kingdom. those speaker features are present in speech in any respect degrees of description: from the spectral info within the sounds to the alternative of phrases and utterances themselves.

This quantity set, LNAI 4343 and LNAI 4441, constitutes a cutting-edge survey for the sector of speaker type. It techniques the subsequent questions: What features of the speaker develop into show up in his or her voice and talking habit? which ones could be inferred from interpreting the acoustic realizations? What can this data be used for? Which equipment are the main appropriate for assorted difficulties during this sector of study? How should still the standard of the implications be evaluated?

The 22 articles of the second one quantity contain a couple of chosen self-contained papers on learn initiatives within the box of speaker class. those comprise between different issues a file on a gender reputation procedure; a examine on emotion attractiveness; a presentation of a text-dependent speaker verification process; an account of the research of either speaker and verbal content material details - in addition to stories on accessory identification.

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Speaker Classification II: Selected Projects

In addition to conveying a message in phrases and sounds, the speech sign consists of information regarding the speaker's personal anatomy, body structure, linguistic adventure and psychological nation. those speaker features are present in speech in any respect degrees of description: from the spectral info within the sounds to the alternative of phrases and utterances themselves.

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Sur. 6 Oth. 5 Oth. 57). Most confusion is between a so-called neutral state and an emotional set. Because we believe there can be different perceptions for a same utterance, we considered an annotator as coherent if he chooses the same labels for the same utterance at any time. We have thus adopted a self re-annotation procedure of small sets of dialogs at different time (for instance once a month) in order to judge the intra-annotator coherence over time. of the utterances are similarly re-annotated [1].

The Anger is worst detected (39%) while still above chance. It is mostly confused with Fear (37%). This might be due to the fact that Fear is often in the background. 5 Discussion and Conclusion We have obtained about 78% and 60% of good detection for respectively lexical and paralinguistic cues on four real-life emotion classes. Both results were better for FearAnxiety detection, which is the most frequent emotion in the corpus and occurs with different intensity (anxiety, stress, fear, panic).

The difference is mainly due to the context. The context is the set of events that are at the origin of a person’s emotions. These events can be external or internal. Different events C. ): Speaker Classification II, LNAI 4441, pp. 34–42, 2007. c Springer-Verlag Berlin Heidelberg 2007 Real-Life Emotion Recognition in Speech 35 might trigger different emotions at the same time: for instance a physical internal event as a stomachache triggering pain with an external event as someone helping the sick person triggering relief.

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