Results 111 to 120 of about 3,610,992 (210)
Speech Emotion Recognition Using Mel-Frequency Cepstral Coefficients
INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTAbstract—Speech Emotion Recognition (SER) has multiple applications in computational psychology, as well as human- computer interaction, and it also plays a major role in these fields. The accuracy of any machine learning technique is greatly impacted by the extraction as well as the appearance of features.
Dev Ankit Kumar +5 more
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Speech synthesis using Mel-Cepstral coefficient feature [PDF]
, 2018 This thesis presents a method to improve quality of synthesized speech by reducing the vocoded effect. The synthesis model takes mel-cepstral coefficients and spectrum envelopes as features of the original speech waveform. Mel-cepstral coefficients could
Wang, Lu
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AUTOMATIC SEGMENTATION OF BROADCAST AUDIO SIGNALS USING AUTO ASSOCIATIVE NEURAL NETWORKS [PDF]
ICTACT Journal on Communication Technology, 2010 In this paper, we describe automatic segmentation methods for audio broadcast data. Today, digital audio applications are part of our everyday lives. Since there are more and more digital audio databases in place these days, the importance of effective ...
P. Dhanalakshmi, S. Palanivel, M. Arul
doaj
, 2018 Emosi merupakan perilaku manusia yang dapat diungkapkan dengan tingkah laku berupa raut wajah dan suara. Suara adalah suatu gelombang longitudinal yang merambat di udara. Pada kehidupan sehari-hari manusia berkomunikasi dengan menggunakan suara. Baik itu
Helmiyah, Siti +2 more
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Emotion Recognition from Speech Signal Using Mel-Frequency Cepstral Coefficients
, 2015 In this paper, mel-frequency cepstral coefficients are investigated for emotional content of speech signal. The features are extracted from spoken utterance.
ATASOY, AYTEN, KORKMAZ, Onur Erdem
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A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient
Dianxin kexue, 2018 The popularity and portability of high-fidelity audio recording equipment and playback equipment poses a serious challenge for speaker recognition systems against playback attacks.Based on the differences between the original speech and the playback ...
Lang LIN +3 more
doaj +2 more sources
Klasifikasi jenis suara manusia menggunakan algoritma Convolutional Neural Network dengan metode ekstraksi Mel-Frequency Cepstral Coefficients [PDF]
Deteksi jenis suara manusia dalam konteks paduan suara sebagai penggunaan media pembelajaran dengan menggunakan CNN dan MFCC. Penelitian ini bertujuan untuk mengklasifikasi jenis suara manusia sehingga terbaginya ke 4 label yaitu sopran, alto, tenor, dan
Fatah, Muhammad Reza Abdul
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A Comparative Investigation of Cepstral Feature Extraction Methods for Deepfake Speech Detection
Applied SciencesThe widespread adoption of voice-based authentication systems has been accompanied by an escalating threat from deep learning-based synthetic speech generation techniques.
Nida Akıncı, Erdal Özbay
doaj +1 more source
ArrayWhile speech spoofing detection techniques based on deep learning have performed well in the recent years, many deep learning-based speech spoofing detection methods based on convolutional neural networks (CNN), Recurrent Neural Networks (RNN), and ...
Rabbia Mahum +5 more
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Evaluation of the Vulnerability of Speaker Verification to Synthetic Speech [PDF]
, 2010 In this paper, we evaluate the vulnerability of a speaker verification (SV) system to synthetic speech. Although this problem was first examined over a decade ago, dramatic improvements in both SV and speech synthesis have renewed interest in this ...
Pucher, M. +4 more
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