Results 81 to 90 of about 372,370 (292)
Objectives. The aim of this study is to develop and analyze parameters for a multifunctional audio module based on the ADAU1701 audio digital signal processor in the SigmaStudio environment.
A. V. Gevorsky +2 more
doaj +1 more source
Reducing Model Complexity for DNN Based Large-Scale Audio Classification
Audio classification is the task of identifying the sound categories that are associated with a given audio signal. This paper presents an investigation on large-scale audio classification based on the recently released AudioSet database.
Lee, Tan, Wu, Yuzhong
core +1 more source
A resonant frequency engineering strategy is proposed to modulate the sensibility of piezoresistive textile‐based tactile sensor. It achieves simultaneous detection of static pressure and dynamic vibrations across an unprecedented bandwidth of 5–600 Hz, surpassing human sensation, therefore enables rapid and precise braille recognition.
Xianhong Zheng +17 more
wiley +1 more source
A dual‐laser‐architected vertical graphene film enables high‐performance, morphologically reconfigurable thermoacoustic loudspeakers.The vertically aligned graphene structures combine efficient heat dissipation, thickness‐independent SPL, and kirigami‐driven 3D transformations, offering shape‐programmable, stretchable, and omnidirectional acoustic ...
TaeGyeong Lim +11 more
wiley +1 more source
New Advances in Audio Signal Processing
The growth in computing capabilities has significantly transformed the realm of data analysis and processing, most notably through the widespread adoption of artificial intelligence (AI) and deep learning technologies [...]
Giovanni Costantini +2 more
doaj +1 more source
A Generative Product-of-Filters Model of Audio [PDF]
We propose the product-of-filters (PoF) model, a generative model that decomposes audio spectra as sparse linear combinations of "filters" in the log-spectral domain.
Hoffman, Matthew D. +2 more
core
Deep Learning for Audio Signal Processing
Given the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing.
Chang, Shuo-yiin +5 more
core +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Robust and secure systems for audio signals
Audio steganography is considered a crucial technique for bolstering information security. It is used to hide sensitive data within an audio signal. This paper presents two robust techniques for audio steganography, which embed secret images within the ...
Marwa A. Nasr +5 more
doaj +1 more source
Inpainting of long audio segments with similarity graphs
We present a novel method for the compensation of long duration data loss in audio signals, in particular music. The concealment of such signal defects is based on a graph that encodes signal structure in terms of time-persistent spectral similarity.
Balazs, Peter +3 more
core +1 more source

