Ses duygu tanima sistemlerinde öznitelik seçme yöntemlerinin karşilaştirilmasi

Tolga Atalay; Deger Ayata; Yusuf Yaslan

doi:10.1109/SIU.2018.8404777

Ses duygu tanima sistemlerinde öznitelik seçme yöntemlerinin karşilaştirilmasi

Tolga Atalay, Deger Ayata, Yusuf Yaslan

Bilgisayar Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

1 Atıf (Scopus)

Özet

The aim of this paper to compare the effect of feature selection methods in emotion recognition from speech and song. Emotion recognition composes of signal processing, feature extraction and classification steps. Nowadays, many studies have focused on common features of speech and song, and have used sub-task classification approach for these systems. In this paper, speech and song data are merged and processed together to focus on the feature selection phase. Autoencoder, Relief-F and Chi-Square selection methods are selected to increase the accuracy of classification. Although selecting features can output similar results, using Relief-F method and Mel Frequency Cepstral Coefficient type of feature outperform these already achieved accuracy rates.

Tercüme edilen katkı başlığı	Comparison of feature selection methods in voice based emotion recognition systems
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	1-4
Sayfa sayısı	4
ISBN (Elektronik)	9781538615010
DOI'lar	https://doi.org/10.1109/SIU.2018.8404777
Yayın durumu	Yayınlandı - 5 Tem 2018
Etkinlik	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 - Izmir, Turkey Süre: 2 May 2018 → 5 May 2018

Yayın serisi

Adı	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
Ülke/Bölge	Turkey
Şehir	Izmir
Periyot	2/05/18 → 5/05/18

Bibliyografik not

Publisher Copyright:
© 2018 IEEE.

Keywords

AutoEncoder
Chi-Square
Cross corpus
Emotion recognition
Feature learning
Feature selection
Relief-F
Signal processing

Belgeye Erişim

10.1109/SIU.2018.8404777

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Atalay, T., Ayata, D., & Yaslan, Y. (2018). Ses duygu tanima sistemlerinde öznitelik seçme yöntemlerinin karşilaştirilmasi. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 (pp. 1-4). (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2018.8404777

@inproceedings{4aceb7fe38534ef79eb35f0690298b2f,

title = "Ses duygu tanima sistemlerinde {\"o}znitelik se{\c c}me y{\"o}ntemlerinin kar{\c s}ila{\c s}tirilmasi",

abstract = "The aim of this paper to compare the effect of feature selection methods in emotion recognition from speech and song. Emotion recognition composes of signal processing, feature extraction and classification steps. Nowadays, many studies have focused on common features of speech and song, and have used sub-task classification approach for these systems. In this paper, speech and song data are merged and processed together to focus on the feature selection phase. Autoencoder, Relief-F and Chi-Square selection methods are selected to increase the accuracy of classification. Although selecting features can output similar results, using Relief-F method and Mel Frequency Cepstral Coefficient type of feature outperform these already achieved accuracy rates.",

keywords = "AutoEncoder, Chi-Square, Cross corpus, Emotion recognition, Feature learning, Feature selection, Relief-F, Signal processing",

author = "Tolga Atalay and Deger Ayata and Yusuf Yaslan",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 ; Conference date: 02-05-2018 Through 05-05-2018",

year = "2018",

month = jul,

day = "5",

doi = "10.1109/SIU.2018.8404777",

language = "T{\"u}rk{\c c}e",

series = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--4",

booktitle = "26th IEEE Signal Processing and Communications Applications Conference, SIU 2018",

address = "United States",

}

Atalay, T, Ayata, D & Yaslan, Y 2018, Ses duygu tanima sistemlerinde öznitelik seçme yöntemlerinin karşilaştirilmasi. in 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, Izmir, Turkey, 2/05/18. https://doi.org/10.1109/SIU.2018.8404777

Ses duygu tanima sistemlerinde öznitelik seçme yöntemlerinin karşilaştirilmasi. / Atalay, Tolga; Ayata, Deger; Yaslan, Yusuf.
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

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AU - Atalay, Tolga

AU - Ayata, Deger

AU - Yaslan, Yusuf

PY - 2018/7/5

Y1 - 2018/7/5

N2 - The aim of this paper to compare the effect of feature selection methods in emotion recognition from speech and song. Emotion recognition composes of signal processing, feature extraction and classification steps. Nowadays, many studies have focused on common features of speech and song, and have used sub-task classification approach for these systems. In this paper, speech and song data are merged and processed together to focus on the feature selection phase. Autoencoder, Relief-F and Chi-Square selection methods are selected to increase the accuracy of classification. Although selecting features can output similar results, using Relief-F method and Mel Frequency Cepstral Coefficient type of feature outperform these already achieved accuracy rates.

AB - The aim of this paper to compare the effect of feature selection methods in emotion recognition from speech and song. Emotion recognition composes of signal processing, feature extraction and classification steps. Nowadays, many studies have focused on common features of speech and song, and have used sub-task classification approach for these systems. In this paper, speech and song data are merged and processed together to focus on the feature selection phase. Autoencoder, Relief-F and Chi-Square selection methods are selected to increase the accuracy of classification. Although selecting features can output similar results, using Relief-F method and Mel Frequency Cepstral Coefficient type of feature outperform these already achieved accuracy rates.

KW - AutoEncoder

KW - Chi-Square

KW - Cross corpus

KW - Emotion recognition

KW - Feature learning

KW - Feature selection

KW - Relief-F

KW - Signal processing

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M3 - Konferans katkısı

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Atalay T, Ayata D, Yaslan Y. Ses duygu tanima sistemlerinde öznitelik seçme yöntemlerinin karşilaştirilmasi. In 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-4. (26th IEEE Signal Processing and Communications Applications Conference, SIU 2018). doi: 10.1109/SIU.2018.8404777

Ses duygu tanima sistemlerinde öznitelik seçme yöntemlerinin karşilaştirilmasi

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap