Results 71 to 80 of about 3,467 (180)

Emotion Recognition of Speech Signals Based on Filter Methods [PDF]

Journal of Intelligent Procedures in Electrical Technology, 2016
Speech is the basic mean of communication among human beings.With the increase of transaction between human and machine, necessity of automatic dialogue and removing human factor has been considered.
Narjes Yazdanian, Hamid Mahmoodian
doaj  

Voice spoofing detection using a neural networks assembly considering spectrograms and mel frequency cepstral coefficients. [PDF]

PeerJ Comput Sci, 2023
Hernández-Nava CA, Rincón-García EA, Lara-Velázquez P, de-Los-Cobos-Silva SG, Gutiérrez-Andrade MA, Mora-Gutiérrez RA.   +5 more
europepmc   +1 more source

Time Series-Based Spoof Speech Detection Using Long Short-Term Memory and Bidirectional Long Short-Term Memory

ARO-The Scientific Journal of Koya University
Detecting fake speech in voice-based authentication systems is crucial for reliability. Traditional methods often struggle because they can't handle the complex patterns over time.
Arsalan R. Mirza, Abdulbasit K. Al-Talabani   +1 more
doaj   +1 more source

A robust deep learning model for fall action detection using healthcare wearable sensors [PDF]

PeerJ Computer Science
The proposed technique begins with Butterworth’s sixth-order filtering of the data followed by segmentation through Hamming window application. The identification of essential patterns is achieved through the utilization of feature extraction methods ...
Abdulwahab Alazeb, Iqra Aijaz Abro, Naif Al Mudawi, Haita F. Alhasson, Naif S. Alshassari, Mohammed Alshehri, Fatimah Alhayan   +6 more
doaj   +2 more sources

ECG Biometrics on Mobile Devices: High-Accuracy Authentication Using i-Vectors and Cepstral Coefficients

IEEE Access
In recent years, the growing importance of personal data security has led to a rapid increase in demand for biometric authentication systems. This study proposes a biometric authentication method based on electrocardiogram (ECG) data that holds potential
F. Saba Kockan, Bulent Bolat
doaj   +1 more source

The Use of Mel-frequency Cepstral Coefficients in Musical Instrument Identification.

, 2008
This paper examines the use of Mel-frequency Cepstral Coefficients in the classification of musical instruments. 2004 piano, violin and flute samples are analysed to get their coefficients. These coefficients are reduced using principal component analysis and used to train a multi-layered perceptron.
Loughran, Róisín, Walker, Jacqueline, O'Neill, Michael, O'Farrell, Marion   +3 more
openaire   +2 more sources

Musical instrument identification using multiscale Mel-frequency cepstral coefficients. [PDF]

, 2010
We investigate the benefits of evaluating Mel-frequency cepstral coefficients (MFCCs) over several time scalesin the context of automatic musical instrument identificationfor signals that are monophonic but derived from real musical settings.We define several sets of features derived from MFCCs computed using multiple time resolutions,and compare their
Sturm, Bob L., Morvidone, Marcela, Daudet, Laurent   +2 more
openaire   +1 more source

AI-detected auditory findings of depression and suicide risk [PDF]

Brazilian Journal of Psychiatry
Objective: Suicide is a major global health concern and one of the leading causes of preventable death. Currently, there is a lack of objective data to assess suicide risk in individuals with depression.
Sena Ozden, Mustafa Sert, Şakir Gica, Orhan Cinar, Irmak Uzun Bayar, Ayhan Yahya Acar, Mehmet Ak   +6 more
doaj   +2 more sources

Raga Identification Using Mel Frequency Cepstral Coefficient

International Journal of Innovations in Engineering and Science, 2023
Kavita. S. Patil, Pramod J. Deore, V. S. Kharote   +2 more
openaire   +1 more source

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