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Speech emotion recognition by using complex MFCC and deep sequential model · Study

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ArticleSpeech emotion recognition by using complex MFCC and deep sequential model

Suprava Patnaik2022

Article2022

Speech emotion recognition by using complex MFCC and deep sequential model

Suprava Patnaik

60 citations·0/0 files stored·Multimedia Tools and Applications

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Emotion and Mood Recognition Speech Recognition and Synthesis Speech and Audio Processing

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References

2005A database of German emotional speech 2010Survey on speech emotion recognition: Features, classification schemes, and databases 2018The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English 2006Emotional speech recognition: Resources, features, and methods 2016Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network 2014Speech emotion recognition using deep neural network and extreme learning machine 2017Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching 2012Features and classifiers for emotion recognition from speech: a survey from 2000 to 2011

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Details

Year2022

Typearticle

Published2022-09-12

VenueMultimedia Tools and Applications

ISSN-L1380-7501

Languageen

Citations60

Files0 public / 0

ShelfEmotion and Mood Recognition

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doi10.1007/s11042-022-13725-y

openalex_workW4296523924

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