Results 1 to 10 of about 29,645 (311)
A Machine Learning Approach to Voice-Based Parkinson Disease Screening Using Multiview Spectrogram and Speech Recognition Features: Diagnostic Study [PDF]
JMIR Medical InformaticsBackgroundParkinson disease frequently manifests early vocal impairment, motivating the development of noninvasive and scalable digital screening tools.
Arifa Zahir +5 more
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Radio Frequency Interference Detection and Mitigation Algorithms Based on Spectrogram Analysis
Algorithms, 2011 Radio Frequency Interference (RFI) detection and mitigation algorithms based on a signal’s spectrogram (frequency and time domain representation) are presented.
Adriano Camps, Camps Adriano
exaly +3 more sources
Elektronika ir Elektrotechnika, 2022 Three main approaches on how audio signals can be used as input to a deep learning model are: extracting hand-crafted features from audio signals, mapping audio signals into appropriate images such as spectrogram-like ones, and using directly raw audio ...
Dejan G. Ciric +3 more
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Spectrogram Analysis of Genomes [PDF]
EURASIP Journal on Advances in Signal Processing, 2004 We performed frequency-domain analysis in the genomes of various organisms using tricolor spectrograms, identifying several types of distinct visual patterns characterizing specific DNA regions. We relate patterns and their frequency characteristics to the sequence characteristics of the DNA.
David Sussillo +2 more
openaire +3 more sources
EURASIP Journal on Advances in Signal Processing, 2010 A novel method, called adaptive pulse coupled neural network (AD-PCNN) using a two-stage denoising strategy, is proposed to reduce noise and speckle in the spectrograms of Doppler blood flow signals.
Haiyan Li, Yufeng Zhang, Dan Xu
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Spectrograms Are Sequences of Patches
CoRR, 2022 Self-supervised pre-training models have been used successfully in several machine learning domains. However, only a tiny amount of work is related to music. In our work, we treat a spectrogram of music as a series of patches and design a self-supervised model that captures the features of these sequential patches: Patchifier, which makes good use of ...
Leyi Zhao, Yi Li
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Multibeam Doppler Sensor-Based Non-Contact Heartbeat Detection Using Beam Diversity
IEEE Access, 2022 Heartbeat detection could enable various applications in the medical and health care fields. In particular, non-contact heartbeat detection can be acceptable for those who have difficulty wearing devices, such as burn patients and infants.
Tsukiko Kitagawa +3 more
doaj +1 more source
, 2005 Speech and other natural sounds show high temporal correlation and smooth spectral evolution punctuated by a few, irregular and abrupt changes. In a conventional Hidden Markov Model (HMM), such structure is represented weakly and indirectly through transitions between explicit states representing 'steps' along such smooth changes.
Reyes-Gomez, Manuel +2 more
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A Deep Neural Network Model for Speaker Identification
Applied Sciences, 2021 Speaker identification is a classification task which aims to identify a subject from a given time-series sequential data. Since the speech signal is a continuous one-dimensional time series, most of the current research methods are based on ...
Feng Ye, Jun Yang
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A Proposed Method for the Sound Recognition Process [PDF]
Engineering and Technology Journal, 2018 One of the most important issues in the signal-processing world is the issue of sounds differentiations. It has many applications in identifying the sources of the sounds, and many researches nowadays serves in this field and all of them looking for the ...
Azad Kareem, Marwa Jassim, Mustafa Ali
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