Results 191 to 200 of about 7,229,432 (222)

A comparative analysis of Constant-Q Transform, gammatonegram, and Mel-spectrogram techniques for AI-aided cardiac diagnostics.

Medical Engineering and Physics
Cardiovascular diseases (CVDs) are the leading global cause of death, which requires the early and accurate detection of cardiac abnormalities. Abnormal heart sounds, indicative of potential cardiac problems, pose a challenge due to their low-frequency ...
Mohammed Saddek Mekahlia, M. Fezari, Ahcen Aliouat   +2 more
semanticscholar   +1 more source

An Exploration of Log-Mel Spectrogram and MFCC Features for Alzheimer’s Dementia Recognition from Spontaneous Speech

Spoken Language Technology Workshop, 2021
In this work, we explore the effectiveness of log-Mel spectrogram and MFCC features for Alzheimer’s dementia (AD) recognition on ADReSS challenge dataset.
Amit Meghanani, C. Anoop, A. Ramakrishnan   +2 more
semanticscholar   +1 more source

DMF2Mel: A Dynamic Multiscale Fusion Network for EEG-Driven Mel Spectrogram Reconstruction

ACM Multimedia
Decoding speech from brain signals is a challenging research problem. Although existing technologies have made progress in reconstructing the mel spectrograms of auditory stimuli at the word or letter level, there remain core challenges in the precise ...
Cunhang Fan, Sheng Zhang, Jingjing Zhang, Enrui Liu, Xinhui Li, Gangming Zhao, Zhao Lv   +6 more
semanticscholar   +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
exaly   +3 more sources

EFFICIENT AUDIO SOURCE SEPARATION USING MEL-SPECTROGRAMS

2020
Audio source separation deals with extracting a source of audio from a mixture, for example vocals from a musical recording. Recent strides have been made in the release of the Open-Unmix GitHub project in September of 2019 to provide new researchers with a framework to hit the ground running with state-of-the-art techniques. The base architecture uses
openaire   +1 more source

Audio Forgery Detection Method with Mel Spectrogram

2023 16th International Conference on Information Security and Cryptology (ISCTürkiye), 2023
Hatice Kübra Güç, Beste Üstübioğlu, Arda Üstübioğlu, Güzin Ulutaş   +3 more
openaire   +1 more source

Age Classification Based on Voice Using Mel-Spectrogram and MFCC

2023 24th International Conference on Digital Signal Processing (DSP), 2023
Tariq Al-Maashani, Israel Mendonça, Masayoshi Aritsugi   +2 more
openaire   +1 more source

Cross-Attention-Guided Wavenet for Mel Spectrogram Reconstruction in The ICASSP 2024 Auditory EEG Challenge

2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
This paper provides an overview of our submission to Task 2 of the Auditory EEG Challenge at ICASSP 2024 Signal Processing Grand Challenge (SPGC). We introduce a novel approach, employing a cross-attention-guided WaveNet with a coarse-to-fine generation ...
Yuan Fang, Hao Li, Xueliang Zhang, Fei Chen, Guanglai Gao   +4 more
semanticscholar   +1 more source

Comparative Analysis of MFCC and Mel-Spectrogram Features in Pump Fault Detection Using Autoencoder

2024 2nd International Conference on Computer Graphics and Image Processing (CGIP)
Pump maintenance plays a pivotal role in industrial operations, where timely detection of faults is key to avoiding costly downtimes. This research explores the influence of two audio feature extraction techniques, Mel-Frequency Cepstral Coefficients ...
Amin Shafiq Bin Saharom, Fumiaki Ehara
semanticscholar   +1 more source

Forge Audio Detection Using Keypoint Features on Mel Spectrograms

2022 45th International Conference on Telecommunications and Signal Processing (TSP), 2022
Güzin Ulutas, Gul Tahaoglu, Beste Ustubioglu   +2 more
openaire   +1 more source