Results 71 to 80 of about 2,773 (174)
Crystallization of dmisteinbergite (hexagonal CaAl2Si2O8) from type B CAI analog melt
Meteoritics &Planetary Science, Volume 61, Issue 9, Page 2258-2268, September 2026.Abstract Dmisteinbergite is a metastable polymorph of CaAl2Si2O8, which has been found in calcium−aluminum‐rich inclusions (CAIs) in chondrites, although anorthite is the predominant CaAl2Si2O8 phase in natural type B CAIs. The occurrence/absence of igneous dmisteinbergite would put tighter constraints on the thermal history of CAIs.
Yasuaki Tsuruoka +6 more
wiley +1 more source
Mel-Spectrogram Inversion via Alternating Direction Method of Multipliers
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Accepted to ICASSP ...
Yoshiki Masuyama +2 more
openaire +4 more sources
Ecological InformaticsPassive acoustic monitoring of marine mammal vocalizations often relies on automated detectors to process large quantities of data. Many automated systems use spectrograms as a way to represent acoustic information, including those built on deep ...
Fabio Frazao, Ruth Joy, Michael Dowd
doaj +1 more source
e-Prime: Advances in Electrical Engineering, Electronics and EnergyLike many semi-arid countries around the world, Morocco benefits from ample solar radiance throughout the year. Taking advantage of this significant energy source, the local government has deployed vast photovoltaic installations to cover the nation’s ...
Karom Mohamed +7 more
doaj +1 more source
Mel-FullSubNet: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR
In this work, we propose Mel-FullSubNet, a single-channel Mel-spectrogram denoising and dereverberation network for improving both speech quality and automatic speech recognition (ASR) performance. Mel-FullSubNet takes as input the noisy and reverberant Mel-spectrogram and predicts the corresponding clean Mel-spectrogram.
Zhou, Rui +3 more
openaire +2 more sources
Sound Event Detection for Music Signals Using Gaussian Processes
TecnoLógicas, 2013 In this paper we present a new methodology for detecting sound events in music signals using Gaussian Processes. Our method firstly takes a time-frequency representation, i.e. the spectrogram, of the input audio signal. Secondly the spectrogram dimension
Pablo A. Alvarado-Durán +2 more
doaj
Anomaly Detection of Deepfake Audio Based on Real Audio Using Generative Adversarial Network Model
IEEE AccessDeepfake audio causes damage not only to individuals and companies, but also to nations; therefore, research on deepfake audio detection technology is crucial.
Daeun Song +3 more
doaj +1 more source
Audio Recognition with Graphical Interface-Based Model for Assisted Robotics
Advances in Electrical and Computer EngineeringThis paper presents an optimized audio recognition system designed for a personal database recorded in Romanian by both male and female voices, aiming to assist elderly individuals through integration with assistive robotics.
TELEMBICI, L., RUSU, C.
doaj +1 more source
Multi-Input Speech Emotion Recognition Model Using Mel Spectrogram and GeMAPS. [PDF]
Sensors (Basel), 2023 Toyoshima I +4 more
europepmc +1 more source
A Multi-Feature Fusion Approach for Dialect Identification using 1D CNN
JOIV: International Journal on Informatics VisualizationThe phonological variety of Kurdish, a language with several dialects, poses a distinct problem in automatically identifying dialects. This study examines and evaluates several sound criteria for identifying Kurdish dialects: Badini, Hawrami, and Sorani.
Sarkhel H.Taher Karim +3 more
doaj +1 more source