Results 71 to 80 of about 3,240 (204)
Leveraged Mel Spectrograms Using Harmonic and Percussive Components in Speech Emotion Recognition
SSRN Electronic Journal, 2022 Speech Emotion Recognition (SER) affective technology enables the intelligent embedded devices to interact with sensitivity. Similarly, call centre employees recognise customers' emotions from their pitch, energy, and tone of voice so as to modify their speech for a high-quality interaction with customers.
David Hason Rudd, Huan Huo, Guandong Xu
openaire +3 more sources
Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare +3 more
wiley +1 more source
Detection of Audio Copy-Move-Forgery with Novel Feature Matching on Mel Spectrogram
SSRN Electronic Journal, 2022 Audio copy-move-forgery created by copying one or more segments of an audio file and pasting it in a different position within the same audio is one of the most widely used methods in the field of audio forensics. This type of forgery is easy to apply but difficult to detect in the case of post-processing operations applied to forged speech to hide ...
Beste Ustubioglu +2 more
openaire +2 more sources
, 2023 We propose an optimization-based method for reconstructing a time-domain signal from a low-dimensional spectral representation such as a mel-spectrogram.
Ono, Nobutaka +2 more
core +1 more source
A Machine Learning-Based Approach for Audio Signals Classification using Chebychev Moments and Mel-Coefficients [PDF]
, 2022 This paper proposes a machine learning-based architecture for audio signals classification based on a joint exploitation of the Chebychev moments and the Mel-Frequency Cepstrum Coefficients.
Pallotta L. +4 more
core +1 more source
Snoring Sound Recognition Using Multi-Channel Spectrograms
Archives of AcousticsObstructive sleep apnea-hypopnea syndrome (OSAHS) is a common and high-risk sleep-related breathing disorder. Snoring detection is a simple and non-invasive method. In many studies, the feature maps are obtained by applying a short-time Fourier transform
Ziqiang YE +3 more
doaj +1 more source
Recognizing Semi-Natural and Spontaneous Speech Emotions Using Deep Neural Networks
IEEE Access, 2022 We needed to find deep emotional features to identify emotions from audio signals. Identifying emotions in spontaneous speech is a novel and challenging subject of research.
Ammar Amjad +4 more
doaj +1 more source
Infancy, Volume 31, Issue 4, July/August 2026.ABSTRACT Infants born preterm present a higher likelihood of differences in social and emotional communication. Crying, as the earliest form of human communication, may provide valuable information about early neurodevelopment. Understanding its acoustic characteristics and how caregivers perceive it can help identify early patterns linked to ...
Giselle V. Mannarino +4 more
wiley +1 more source
Comparison results on the mel-spectrogram dataset.
Comparison results on the mel-spectrogram dataset.
Thanh-Cong Truong (18452213) +2 more
core +1 more source
, 2020 In industry, the ability to detect damage or abnormal functioning in machinery is very important. However, manual detection of machine fault sound is economically inefficient and labor-intensive.
Lundgren, Jan +3 more
core +1 more source