TY - GEN
T1 - Assessing an Application of Spontaneous Stressed Speech - Emotions Portal
AU - Palacios-Alonso, Daniel
AU - Lázaro-Carrascosa, Carlos
AU - López-Arribas, Agustín
AU - Meléndez-Morales, Guillermo
AU - Gómez-Rodellar, Andrés
AU - Loro-Álavez, Andrés
AU - Nieto-Lluis, Victor
AU - Rodellar-Biarge, Victoria
AU - Tsanas, Athanasios
AU - Gómez-Vilda, Pedro
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Detecting and identifying emotions expressed in speech signals is a very complex task that generally requires processing a large sample size to extract intricate details and match the diversity of human expression in speech. There is not an emotional dataset commonly accepted as a standard test bench to evaluate the performance of the supervised machine learning algorithms when presented with extracted speech characteristics. This work proposes a generic platform to capture and validate emotional speech. The aim of the platform is collaborative-crowdsourcing and it can be used for any language (currently, it is available in four languages such as Spanish, English, German and French). As an example, a module for elicitation of stress in speech through a set of online interviews and other module for labeling recorded speech have been developed. This study is envisaged as the beginning of an effort to establish a large, cost-free standard speech corpus to assess emotions across multiple languages.
AB - Detecting and identifying emotions expressed in speech signals is a very complex task that generally requires processing a large sample size to extract intricate details and match the diversity of human expression in speech. There is not an emotional dataset commonly accepted as a standard test bench to evaluate the performance of the supervised machine learning algorithms when presented with extracted speech characteristics. This work proposes a generic platform to capture and validate emotional speech. The aim of the platform is collaborative-crowdsourcing and it can be used for any language (currently, it is available in four languages such as Spanish, English, German and French). As an example, a module for elicitation of stress in speech through a set of online interviews and other module for labeling recorded speech have been developed. This study is envisaged as the beginning of an effort to establish a large, cost-free standard speech corpus to assess emotions across multiple languages.
KW - Characterizing stress
KW - Cooperative framework
KW - Data acquisition
KW - Emotional stress
KW - Stress behavior in human-computer interaction
UR - http://www.scopus.com/inward/record.url?scp=85065889834&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-19591-5_16
DO - 10.1007/978-3-030-19591-5_16
M3 - Conference contribution
AN - SCOPUS:85065889834
SN - 9783030195908
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 149
EP - 160
BT - Understanding the Brain Function and Emotions - 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Proceedings
A2 - Adeli, Hojjat
A2 - Ferrández Vicente, José Manuel
A2 - Toledo Moreo, Javier
A2 - Álvarez-Sánchez, José Ramón
A2 - de la Paz López, Félix
PB - Springer
T2 - 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019
Y2 - 3 June 2019 through 7 June 2019
ER -