Results 1 to 10 of about 3,785,484 (384)

Shallow and deep feature fusion for digital audio tampering detection [PDF]

open access: goldEURASIP Journal on Advances in Signal Processing, 2022
Digital audio tampering detection can be used to verify the authenticity of digital audio. However, most current methods use standard electronic network frequency (ENF) databases for visual comparison analysis of ENF continuity of digital audio or ...
Zhifeng Wang   +5 more
openalex   +2 more sources

Sounds of COVID-19: exploring realistic performance of audio-based digital testing [PDF]

open access: greennpj Digital Medicine, 2021
To identify Coronavirus disease (COVID-19) cases efficiently, affordably, and at scale, recent work has shown how audio (including cough, breathing and voice) based approaches can be used for testing. However, there is a lack of exploration of how biases
Jing Han   +11 more
openalex   +3 more sources

Digital Audio Forensics: Microphone and Environment Classification Using Deep Learning

open access: yesIEEE Access, 2021
The recording device along with the acoustic environment plays a major role in digital audio forensics. We propose an acoustic source identification system in this paper, which includes identifying both the recording device and the environment in which ...
Mustafa A. Qamhan   +4 more
semanticscholar   +3 more sources

Digital audio effects [PDF]

open access: yesEURASIP Journal on Advances in Signal Processing, 2010
RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'.
,   +5 more
core   +5 more sources

Digital Audio Developments and Public Value Under Debate: The Case of National and Regional Spanish PSM [PDF]

open access: goldJournalism and Media
Public service media (PSM) are undergoing essential digital transformations to compete in an audiovisual ecosystem dominated by new technological players that have reshaped traditional media consumption habits.
Tania Fernández Lombao   +2 more
openalex   +3 more sources

Digital Audio Tampering Detection Based on Deep Temporal-Spatial Features of Electrical Network Frequency

open access: yesInf., 2023
In recent years, digital audio tampering detection methods by extracting audio electrical network frequency (ENF) features have been widely applied. However, most digital audio tampering detection methods based on ENF have the problems of focusing on ...
Chunyan Zeng   +4 more
semanticscholar   +1 more source

Audio communication in the face of the renaissance of digital audio

open access: yesEl Profesional de la Informacion, 2022
In recent years, digital audio has undergone an explosion. The transformation of radio and its expansion to new channels and consumer devices, added to the rise of podcasts and streaming music platforms, have led to the transformation of the audio ...
Teresa Piñeiro-Otero   +1 more
semanticscholar   +1 more source

Efficient Precoding and Power Allocation Techniques for Maximizing Spectral Efficiency in Beamspace MIMO-NOMA Systems

open access: yesSensors, 2023
Beamspace MIMO-NOMA is an effective way to improve spectral efficiency. This paper focuses on a downlink non-orthogonal multiple access (NOMA) transmission scheme for a beamspace multiple-input multiple-output (MIMO) system.
Yongfei Liu   +4 more
doaj   +1 more source

AUDD: Audio Urdu Digits Dataset for Automatic Audio Urdu Digit Recognition [PDF]

open access: yesApplied Sciences, 2021
The ongoing development of audio datasets for numerous languages has spurred research activities towards designing smart speech recognition systems. A typical speech recognition system can be applied in many emerging applications, such as smartphone dialing, airline reservations, and automatic wheelchairs, among others.
Aisha Chandio   +4 more
openaire   +4 more sources

Method to control the amount of “musical” noise for speech quality assessments

open access: yesActa Acustica, 2023
This study presents a method of adding to clean speech signals a controlled degree of “musical” noise distortions that mimic typical artefacts of speech enhancement systems.
Gößwein Jonathan Albert   +2 more
doaj   +1 more source

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