In recent years, convolutional neural networks (CNNs) have outperformed conventional
methods in end-to-end speaker identification (SI) systems. The CNN training time is …

Speaker recognition is an indispensable technology for biometrics. It distinguishes
individuals based on their vocal patterns. In this paper, a joint confirmation method based on …

Speech recognition is an approach of acknowledging human speech with the aid of the
system and to produce string output in written format. A model is positioned from a crew of …

The aim of this study is to evaluate and compare machine learning algorithms when various
feature extraction techniques are employed together and determine the optimal feature …

Traditional biometric systems are subjected to several attacks. If the original database of
human biometrics is compromised, the biometric data is lost forever. This paper presents a …

Based on the adverse physiological and social consequences associated with sadness,
recognizing this emotion is crucial to mitigate its negative impacts. To address this issue, an …

Automatic speaker recognition is the task of automatically determining or verifying the
identity of a speaker from a recording of his or her speech sample and has been studied for …

Speech recognition plays a major role in technology that enables computers and devices to
understand and interpret human speech, while speaker identification is a specialized …

A speaker identification system based on Mel-frequency cepstral coefficients (MFCC) and a
convolutional neural network (CNN) is proposed in this paper. This paper aims to identify …

Audio signals represent an efficient tool for communication and remote access to systems
such as IoT. These signals are usually used to convey information from the transmitter to the …