Design and implementation of Czech database of speech emotions

Uhrin, Dominik; Partila, Pavol; Chmelikova, Z.; Hlozak, Martin; Orčík, Lukáš

doi:10.1109/telfor.2014.7034463

Cited by 5 publications

(2 citation statements)

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“…For editing and cuting of source recordings, software Audacity was used. By default, Audacity was unable to edit mp3 audio ile; therefore, LAME Encode library had to be installed [11].…”

Section: Sample Database Creationmentioning

confidence: 99%

Design of Emotion Recognition System

Uhrin¹,

Partila²,

Frnda³

et al. 2017

Proceedings of the 2nd Czech-China Scientific Conference 2016

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The chapter deals with a speech emotion recognition system as a complex solution including a Czech speech database of emotion samples in a form of short sound records and the tool evaluating database samples by using subjective methods. The chapter also involves individual components of an emotion recognition system and shortly describes their functions. In order to create the database of emotion samples for learning and training of emotional classiier, it was necessary to extract short sound recordings from radio and TV broadcastings. In the second step, all records in emotion database were evaluated using our designed evaluation tool and results were automatically evaluated how they are credible and reliable and how they represent diferent states of emotions. As a result, three inal databases were formed. The chapter also describes the idea of new potential model of a complex emotion recognition system as a whole unit.

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“…For editing and cuting of source recordings, software Audacity was used. By default, Audacity was unable to edit mp3 audio ile; therefore, LAME Encode library had to be installed [11].…”

Section: Sample Database Creationmentioning

confidence: 99%

Design of Emotion Recognition System

Uhrin¹,

Partila²,

Frnda³

et al. 2017

Proceedings of the 2nd Czech-China Scientific Conference 2016

View full text Add to dashboard Cite

show abstract

“…So far, Slavic language databases of acted emotional speech in Serbian (GEES) (Jovičić et al, 2004), Polish (PES) (Cichosz, 2008; Igras, Ziółko, 2013; Staroniewicz, Majewski, 2009) and Russian (RUS-LANA) (Makarova, Petrushin, 2002) have been compiled. Databases of spontaneous speech have recently been developed in Croatian (CrES) (Dropuljić et al, 2011), Czech (CzED) (Uhrin et al, 2014) and Slovenian (EmoLUKS) (Justin et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Archives of Acoustics

Milošević

Đurović

2020

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Today's human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is of great interest. Literature contains many different, more or less successful forms of these systems. This work emerged as an attempt to clarify which speech features are the most informative, which classification structure is the most convenient for this type of tasks, and the degree to which the results are influenced by database size, quality and cultural characteristic of a language. The research is presented as the case study on Slavic languages.

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Trends in speech emotion recognition: a comprehensive survey

Kaur

Singh

2023

Multimed Tools Appl

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Design and implementation of Czech database of speech emotions

Cited by 5 publications

References 5 publications

Design of Emotion Recognition System

Design of Emotion Recognition System

Archives of Acoustics

Trends in speech emotion recognition: a comprehensive survey

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