Search results

Filters

  • Journals

Search results

Number of results: 1
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

Laughter is one of the most important paralinguistic events, and it has specific roles in human conversation. The automatic detection of laughter occurrences in human speech can aid automatic speech recognition systems as well as some paralinguistic tasks such as emotion detection. In this study we apply Deep Neural Networks (DNN) for laughter detection, as this technology is nowadays considered state-of-the-art in similar tasks like phoneme identification. We carry out our experiments using two corpora containing spontaneous speech in two languages (Hungarian and English). Also, as we find it reasonable that not all frequency regions are required for efficient laughter detection, we will perform feature selection to find the sufficient feature subset.

Go to article

Authors and Affiliations

Gábor Gosztolya
András Beke
Tilda Neuberger
László Tóth

This page uses 'cookies'. Learn more