TranStutter: A Convolution-Free Transformer-Based Deep Learning Method to Classify Stuttered Speech Using 2D Mel-Spectrogram Visualization and Attention-Based Feature Representation. [PDF]
Sensors (Basel), 2023 Basak K, Mishra N, Chang HT.
europepmc +1 more source
Music-induced emotion flow modeling by ENMI Network.
PLoS ONEThe relation between emotions and music is substantial because music as an art can evoke emotions. Music emotion recognition (MER) studies the emotions that music brings in the effort to map musical features to the affective dimensions.
Yunrui Shang +3 more
doaj +1 more source
Multi Pattern Features-Based Spoofing Detection Mechanism Using One Class Learning
IEEE AccessAutomatic Speaker Verification systems are prone to various voice spoofing attacks such as replays, voice conversion (VC) and speech synthesis. Malicious users can perform specific tasks such as controlling the bank account of someone, taking control of ...
Beste Ustubioglu +5 more
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Gender Recognition Based on the Stacking of Different Acoustic Features
Applied SciencesA speech signal can provide various information about a speaker, such as their gender, age, accent, and emotional state. The gender of the speaker is the most salient piece of information contained in the speech signal and is directly or indirectly used ...
Ergün Yücesoy
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Age Prediction from Korean Speech Data Using Neural Networks with Diverse Voice Features
Applied SciencesA person’s voice serves as an indicator of age, as it changes with anatomical and physiological influences throughout their life. Although age prediction is a subject of interest across various disciplines, age-prediction studies using Korean voices are ...
Hayeon Ku +4 more
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Marine Mammal Call Classification Using a Multi-Scale Two-Channel Fusion Network (MT-Resformer)
Journal of Marine Science and EngineeringThe classification of high-frequency marine mammal vocalizations often faces challenges due to the limitations of acoustic features, which are sensitive to mid-to-low frequencies but offer low resolution in high-frequency ranges.
Xiang Li +6 more
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Multi-Label Emotion Recognition of Korean Speech Data Using Deep Fusion Models
Applied SciencesAs speech is the most natural way for humans to express emotions, studies on Speech Emotion Recognition (SER) have been conducted in various ways However, there are some areas for improvement in previous SER studies: (1) while some studies have performed
Seoin Park +3 more
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Leveraging MFCC and Mel-Spectrogram Representations for Deep Learning-Based Speech Recognition
Engineering ProceedingsThis 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
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ESTVocoder: An Excitation-Spectral-Transformed Neural Vocoder Conditioned on Mel Spectrogram
This paper proposes ESTVocoder, a novel excitation-spectral-transformed neural vocoder within the framework of source-filter theory. The ESTVocoder transforms the amplitude and phase spectra of the excitation into the corresponding speech amplitude and phase spectra using a neural filter whose backbone is ConvNeXt v2 blocks.
Xiao-Hang Jiang +4 more
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Frontiers in PhysiologyIntroductionSnoring is a common symptom of Obstructive Sleep Apnea (OSA) and has also been associated with an elevated risk of cerebrovascular disease. However, existing snoring detection studies predominantly focus on individuals with Obstructive Sleep ...
Caijian Hua +4 more
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