Affective and behavioural computing: Lessons learnt from the first computational paralinguistics challenge
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 …
(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 …
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 …
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 …
области компьютерной паралингвистики, а также последних достижений …
An end-to-end approach to joint social signal detection and automatic speech recognition
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 …
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
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 …
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 …
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 …
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 …
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 …
However, the effect of the mobile phone on both the process of and, also, the non-verbal …