Laughter Inquisition in Affect Recognition
نویسنده
چکیده
Laughter and humor are major ingredients of humanity but does not have any black and white authenticate. Laughter is a physiological process, which activates facial, respiratory and laryngeal muscles. Laughter may occur instinctively in response to humor or to appropriate emotional or sociological stimuli and can also be elicited upon command – voluntary, contrived or faked laughter. Exploring the pattern of laughter is an intricate and arduous errand. Speech and laughter are quite disparate in the vocalization, duration and in regularity of its occurrence. This work is a convincing attempt to catalog the different types of laughter as positive laughter, negative laughter, laughed speech and vague category. Feature selection was done using Radial Basis Boltzmann Machine Network, categorization was done using an ErgodicHidden Markov Model. The corpus used for experimental study was the International Computer Science Institute (ICSI) Meeting Corpus from which 30 meetings were taken as the data set. The technique used has yielded a persuasive result in categorizing the types of laughter.
منابع مشابه
Building a Multimodal Laughter Database for Emotion Recognition
Laughter is a significant paralinguistic cue that is largely ignored in multimodal affect analysis. In this work, we investigate how a multimodal laughter corpus can be constructed and annotated both with discrete and dimensional labels of emotions for acted and spontaneous laughter. Professional actors enacted emotions to produce acted clips, while spontaneous laughter was collected from volun...
متن کاملDemonstrating Laughter Detection in Natural Discourses
This work focuses on the demonstration of previously achieved results in the automatic detection of laughter from natural discourses. In the previous work features of two different modalities, namely audio and video from unobtrusive sources, were used to build a system of recurrent neural networks called Echo State networks to model the dynamics of laughter. This model was then again utilized t...
متن کاملAnalysis of the occurrence of laughter in meetings
Automatic speech understanding in natural multiparty conversation settings stands to gain from parsing not only verbal but also non-verbal vocal communicative behaviors. In this work, we study the most frequently annotated non-verbal behavior, laughter, whose detection has clear implications for speech understanding tasks, and for the automatic recognition of affect in particular. To complement...
متن کاملAutomatic laughter detection using neural networks
Laughter recognition is an underexplored area of research. Our goal in this work was to develop an accurate and efficient method to recognize laughter segments, ultimately for the purpose of speaker recognition. Previous work has classified presegmented data as to the presence of laughter using SVMs, GMMs, and HMMs. In this work, we have extended the stateof-the-art in laughter recognition by e...
متن کاملSocial Context Disambiguates the Interpretation of Laughter
Despite being a pan-cultural phenomenon, laughter is arguably the least understood behaviour deployed in social interaction. As well as being a response to humour, it has other important functions including promoting social affiliation, developing cooperation and regulating competitive behaviours. This multi-functional feature of laughter marks it as an adaptive behaviour central to facilitatin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008