Affective and behavioural computing: Lessons learnt from the first computational paralinguistics challenge

B Schuller, F Weninger, Y Zhang, F Ringeval… - Computer Speech & …, 2019 - Elsevier
In this article, we review the INTERSPEECH 2013 Computational Paralinguistics ChallengE
(ComParE)–the first of its kind–in light of the recent developments in affective and …

Social signal classification using deep BLSTM recurrent neural networks

R Brueckner, B Schulter - 2014 IEEE international conference …, 2014 - ieeexplore.ieee.org
Non-verbal speech cues play an important role in human communication such as
expressing emotional states or maintaining the conversational flow. In this paper we …

[PDF][PDF] Non-Verbal Vocalisation and Laughter Detection Using Sequence-to-Sequence Models and Multi-Label Training.

S Condron, G Clarke, A Klementiev, D Morse-Kopp… - Interspeech, 2021 - isca-archive.org
Non-verbal vocalisations (NVVs) such as laughter are an important part of communication in
social interactions and carry important information about a speaker's state or intention. There …

Актуальные задачи и достижения систем паралингвистического анализа речи

АА Карпов, Х Кайа, АА Салах - Научно-технический вестник …, 2016 - cyberleninka.ru
Представлен аналитической обзор современных и актуальных задач, стоящих в
области компьютерной паралингвистики, а также последних достижений …

An end-to-end approach to joint social signal detection and automatic speech recognition

H Inaguma, M Mimura, K Inoue, K Yoshii… - … , Speech and Signal …, 2018 - ieeexplore.ieee.org
Social signals such as laughter and fillers are often observed in natural conversation, and
they play various roles in human-to-human communication. Detecting these events is useful …

Classification of social signals using deep LSTM-based recurrent neural networks

H Joshi, A Verma, A Mishra - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
Non-linguistic speech cues aid expression of various emotions in human communication. In
this work, we demonstrate the application of deep long short-term memory (LSTM) recurrent …

State-of-the-art tasks and achievements of paralinguistic speech analysis systems

A Karpov Alexey, K Heysem - Journal Scientific and Technical Of …, 2016 - ntv.ifmo.ru
We present analytical survey of state-of-the-art actual tasks in the area of computational
paralinguistics, as well as the recent achievements of automatic systems for paralinguistic …

[图书][B] Non-linguistic Vocalization Recognition Based on Convolutional, Long Short-Term Memory, Deep Neural Networks

L Qiu - 2018 - search.proquest.com
Abstract Non-linguistic Vocalization Recognition refers to the detection and classification of
non-speech voice such as laughter, sneeze, cough, cry, screaming, etc. It could be seen as …

Application of deep learning methods in computational paralinguistics

RC Brückner - 2020 - mediatum.ub.tum.de
This thesis explores and proposes new approaches of deep learning methods adopting
deep feed-forward, convolutional, and recurrent neural networks to common problems of …

[PDF][PDF] The SSPNet-Mobile Corpus: from the detection of non-verbal cues to the inference of social behaviour during mobile phone conversations

A Polychroniou - 2014 - theses.gla.ac.uk
Mobile phones are one of the main channels of communication in contemporary society.
However, the effect of the mobile phone on both the process of and, also, the non-verbal …