Modelling of emotion recognition system from speech using MFCC features
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Publisher
AIP Publishing
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0066503
Reference18 articles.
1. Detection and Analysis of Emotion from Speech Signals
2. Gupta, Shikha, Jafreezal Jaafar, WF Wan Ahmad, and Arpit Bansal. “Feature extraction using MFCC.” Signal & Image Processing: An International Journal (SIPIJ) 4, no. 4 (2013): 101–108.
3. Rajasekhar, Ashwini, and Malaya Kumar Hota. “A study of speech, speaker and emotion recognition using Mel frequency cepstrum coefficients and support vector machines.” In 2018 International Conference on Communication and Signal Processing (ICCSP), pp. 0114–0118. IEEE, 2018.
4. Raghib, Omar, Eshita Sharma, Tameem Ahmad, and Faisal Alam. “Emotion analysis and speech signal processing.” In 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), pp. 2872–2875. IEEE, 2017.
5. Hidayat, Risanuri, Agus Bejo, Sujoko Sumaryono, and Anggun Winursito. “Denoising speech for mfcc feature extraction using wavelet transformation in speech recognition system.” In 2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 280–284. IEEE, 2018.
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