Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …

Children speech recognition is challenging mainly due to the inherent high variability in
children's physical and articulatory characteristics and expressions. This variability manifests …

In this work, a Punjabi children speech recognition system is developed under different
acoustic matched and mismatched conditions. One major problem in children's speech …

Adult-targeted automatic speech recognition (ASR) has made significant advancements in
recent years and can produce speech-to-text output with very low word-error-rate, for …

Accepted: 13 June 2021 Most of the automatic speech recognition (ASR) systems are
trained using adult speech due to the less availability of the children's speech dataset. The …

Even as modern indoor positioning systems become more precise and computationally
lightweight, most rely on specific infrastructure to be installed, leading to increased setup …

Anomaly identification of wind turbine blades is crucial for reducing the maintenance and
operational costs of wind turbines. A method based on Mel-Spectrogram Difference feature …

A kind of learnable parametric filter banks is proposed in this paper. Parametric filter banks
refer to selecting learnable parameters from the original filter banks and learning a …

The Mel-frequency Cepstral Coefficients (MFCC) method is the most popular method and
has good performance as a feature extraction to date. But based on the simulation results, it …

Voice biometric systems are being used in various applications for secure user
authentication using automatic speaker verification technology. However, these systems are …