Emotion Classification of Voice Recordings Using Deep Learning
In this work, we present methods for voice emotion classification using deep learning techniques. To processing audio signals, our method leverages spectral features of voice recordings, which are known to serve as powerful representations of temporal signals. To tackling the classification task, we...
| Main Author: | |
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| Format: | Article |
| Language: | English |
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Gitutyun
2022-06-01
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| Series: | Mathematical Problems of Computer Science |
| Subjects: | |
| Online Access: | http://mpcs.sci.am/index.php/mpcs/article/view/730 |
| _version_ | 1818496775646871552 |
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| author | Narek T. Tumanyan |
| author_facet | Narek T. Tumanyan |
| author_sort | Narek T. Tumanyan |
| collection | DOAJ |
| description | In this work, we present methods for voice emotion classification using deep learning techniques. To processing audio signals, our method leverages spectral features of voice recordings, which are known to serve as powerful representations of temporal signals. To tackling the classification task, we consider two approaches to processing spectral features: as temporal signals and as spatial/2D signals. For each processing method, we use different neural network architectures that fit the approach. Classification results are analyzed and insights are presented. |
| first_indexed | 2024-12-10T18:37:12Z |
| format | Article |
| id | doaj.art-3128144367bb4db09dbc502f977bf9c5 |
| institution | Directory Open Access Journal |
| issn | 2579-2784 2738-2788 |
| language | English |
| last_indexed | 2024-12-10T18:37:12Z |
| publishDate | 2022-06-01 |
| publisher | Gitutyun |
| record_format | Article |
| series | Mathematical Problems of Computer Science |
| spelling | doaj.art-3128144367bb4db09dbc502f977bf9c52022-12-22T01:37:47ZengGitutyunMathematical Problems of Computer Science2579-27842738-27882022-06-015771710.51408/1963-0082730Emotion Classification of Voice Recordings Using Deep LearningNarek T. Tumanyan0Weizmann Institute of ScienceIn this work, we present methods for voice emotion classification using deep learning techniques. To processing audio signals, our method leverages spectral features of voice recordings, which are known to serve as powerful representations of temporal signals. To tackling the classification task, we consider two approaches to processing spectral features: as temporal signals and as spatial/2D signals. For each processing method, we use different neural network architectures that fit the approach. Classification results are analyzed and insights are presented.http://mpcs.sci.am/index.php/mpcs/article/view/730voice sentiment detectionmood recognitionspeech emotion recognitioncepstral features |
| spellingShingle | Narek T. Tumanyan Emotion Classification of Voice Recordings Using Deep Learning Mathematical Problems of Computer Science voice sentiment detection mood recognition speech emotion recognition cepstral features |
| title | Emotion Classification of Voice Recordings Using Deep Learning |
| title_full | Emotion Classification of Voice Recordings Using Deep Learning |
| title_fullStr | Emotion Classification of Voice Recordings Using Deep Learning |
| title_full_unstemmed | Emotion Classification of Voice Recordings Using Deep Learning |
| title_short | Emotion Classification of Voice Recordings Using Deep Learning |
| title_sort | emotion classification of voice recordings using deep learning |
| topic | voice sentiment detection mood recognition speech emotion recognition cepstral features |
| url | http://mpcs.sci.am/index.php/mpcs/article/view/730 |
| work_keys_str_mv | AT narekttumanyan emotionclassificationofvoicerecordingsusingdeeplearning |