An Analysis of Rhythmic Staccato-Vocalization Based on Frequency Demodulation for Laughter Detection in Conversational Meetings

Human laugh is able to convey various kinds of meanings in human communications. There exists various kinds of human laugh signal, for example: vocalized laugh and non vocalized laugh. Following the theories of psychology, among all the vocalized laugh type, rhythmic staccato-vocalization significantly evokes the positive responses in the interactions. In this paper we attempt to exploit this observation to detect human laugh occurrences, i.e., the laughter, in multiparty conversations from the AMI meeting corpus. First, we separate the high energy frames from speech, leaving out the low energy frames through power spectral density estimation. We borrow the algorithm of rhythm detection from the area of music analysis to use that on the high energy frames. Finally, we detect rhythmic laugh frames, analyzing the candidate rhythmic frames using statistics. This novel approach for detection of `positive' rhythmic human laughter performs better than the standard laughter classification baseline.Comment: 5 pages, 1 figure, conference pape

Comparing Annotations of Non-verbal Vocalisations in Speech Corpora

In this study eleven corpora of spontaneous and scripted speech (in English and in German) are analysed regarding their annotation inventories of selected highly frequent nonverbal vocalisations (NVVs). It appears that only one corpus considers all NVVs and that laughter is the only NVV annotated in all corpora. The findings lead to a discussion of possible reasons for this situation. In conclusion it is argued that a wider distribution and more consistency is needed with respect to the annotation of NVVs

Comparing Annotations of Non-verbal Vocalisations in Speech Corpora

In this study eleven corpora of spontaneous and scripted speech (in English and in German) are analysed regarding their annotation inventories of selected highly frequent nonverbal vocalisations (NVVs). It appears that only one corpus considers all NVVs and that laughter is the only NVV annotated in all corpora. The findings lead to a discussion of possible reasons for this situation. In conclusion it is argued that a wider distribution and more consistency is needed with respect to the annotation of NVVs

French Face-to-Face Interaction: Repetition as a Multimodal Resource

International audienceIn this chapter, after presenting the corpus as well as some of theannotations developed in the OTIM project, we then focus on the specificphenomenon of repetition. After briefly discussing this notion, we showthat different degrees of convergence can be achieved by speakersdepending on the multimodal complexity of the repetition and on thetiming in between the repeated element and the model. Although we focusmore specifically on the gestural level, we present a multimodal analysis ofgestural repetitions in which we met several issues linked to multimodalannotations of any type. This gives an overview of crucial issues in crosslevellinguistic annotation, such as the definition of a phenomenonincluding formal and/or functional categorization

Proceedings

Proceedings of the 3rd Nordic Symposium on Multimodal Communication. Editors: Patrizia Paggio, Elisabeth Ahlsén, Jens Allwood, Kristiina Jokinen, Costanza Navarretta. NEALT Proceedings Series, Vol. 15 (2011), vi+87 pp. © 2011 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/22532

Laughter Dynamics in Dyadic Conversations

Ludusan B, Wagner P. Laughter Dynamics in Dyadic Conversations. In: Proceedings of Interspeech. 2019.Human verbal communication is a complex phenomenon involving dynamics that normally result in the alignment of participants on several modalities, and across various linguistic domains. We examined here whether such dynamics occur also for paralinguistic events, in particular, in the case of laughter. Using a conversational corpus containing dyadic interactions in three languages (French, German and Mandarin Chinese), we investigated three measures of alignment: convergence, synchrony and agreement. Support for convergence and synchrony was found in all three languages, although the level of support varied with the language, while the agreement in laughter type was found to be significant for the German data. The implications of these findings towards a better understanding of the role of laughter in human communication are discussed