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
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Сучасний стан наукових досліджень та технологій в промисловості, 2023 The subject matter of the study is the analysis of the influence of pre-processing stages of the audio on the accuracy of speaker language regognition. The importance of audio pre-processing has grown significantly in recent years due to its key role in
Olesia Barkovska, Anton Havrashenko
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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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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
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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
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Voice Disorder Classification Based on Multitaper Mel Frequency Cepstral Coefficients Features. [PDF]
Comput Math Methods Med, 2015 Eskidere Ö, Gürhanlı A.
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Voice Recognition and Marking Using Mel-frequency Cepstral Coefficients [PDF]
Sensors and Materials, 2020 Sheu, Jia-Shing, Chen, Ching-Wen
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Advancing insect monitoring: analysis of mel-frequency cepstral coefficients from optical signals for body orientation estimation. [PDF]
Appl Phys BSaha T, Thomas BP.
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Rapid Diagnosis of Distributed Acoustic Sensing Vibration Signals Using Mel-Frequency Cepstral Coefficients and Liquid Neural Networks. [PDF]
Sensors (Basel)Liu H, Xu Y, Qi Y, Yang H, Bi W.
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Enhanced heart sound classification using Mel frequency cepstral coefficients and comparative analysis of single vs. ensemble classifier strategies. [PDF]
PLoS OneHosseinzadeh M +10 more
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