Results 91 to 100 of about 3,790,103 (166)
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 +1 more
doaj +1 more source
Leveraging MFCC and Mel-Spectrogram Representations for Deep Learning-Based Speech Recognition
This work propose an audio feature pipeline to support machine learning tasks through the extraction of the Mel Frequency Cepstral Coefficients and Mel-spectrogram which is then used as the input of an Convolutional Neural Network which is trained to ...
Jose Antonio Lopez-Olvera +3 more
doaj +1 more source
Emotion Recognition of Speech Signals Based on Filter Methods [PDF]
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
Применение mel-кепстрального метода для идентификации акустических сигналов БПЛА [PDF]
This report describes the work of calculating the Mel-Frequency Cepstral Coefficients (MFCC). Measurements of characteristics were performed on a real model.
Калиновский, Р. В.
core
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
A robust deep learning model for fall action detection using healthcare wearable sensors [PDF]
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 +6 more
doaj +2 more sources
Implementation of Mel-Frequency Cepstral Coefficient As Feature Extraction Method On Speech Audio Data [PDF]
Sounds cannot be directly processed by machines without a feature extraction process being carried out first. Currently, there are so many choices of feature extraction methods that can be used, so determining the right feature extraction method is not ...
Kodong, Frans Richard +2 more
core +1 more source
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
core +1 more source
Speech synthesis using Mel-Cepstral coefficient feature [PDF]
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
core
Raga Identification Using Mel Frequency Cepstral Coefficient
Kavita. S. Patil +2 more
openaire +1 more source

