AIMC Topic: Acoustics

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Deep Neural Network for Automatic Classification of Pathological Voice Signals.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Computer-aided pathological voice detection is efficient for initial screening of pathological voice, and has received high academic and clinical attention. This paper proposes an automatic diagnosis method of pathological voice based on ...

Characterizing soundscapes across diverse ecosystems using a universal acoustic feature set.

Proceedings of the National Academy of Sciences of the United States of America
Natural habitats are being impacted by human pressures at an alarming rate. Monitoring these ecosystem-level changes often requires labor-intensive surveys that are unable to detect rapid or unanticipated environmental changes. Here we have developed...

The acoustic near-field measurement of aye-ayes' biological auditory system utilizing a biomimetic robotic tap-scanning.

Bioinspiration & biomimetics
The aye-aye (Daubentonia madagascariensis) is best known for its unique acoustic-based foraging behavior called 'tap-scanning' or 'percussive foraging'. The tap-scanning is a unique behavior allowing aye-aye to locate small cavities beneath tree bark...

Learning to localize sounds in a highly reverberant environment: Machine-learning tracking of dolphin whistle-like sounds in a pool.

PloS one
Tracking the origin of propagating wave signals in an environment with complex reflective surfaces is, in its full generality, a nearly intractable problem which has engendered multiple domain-specific literatures. We posit that, if the environment a...

Classification of Dried Strawberry by the Analysis of the Acoustic Sound with Artificial Neural Networks.

Sensors (Basel, Switzerland)
In this paper, the authors used an acoustic wave acting as a disturbance (acoustic vibration), which travelled in all directions on the whole surface of a dried strawberry fruit in its specified area. The area of space in which the acoustic wave occu...

Ultrasonic liver steatosis quantification by a learning-based acoustic model from a novel shear wave sequence.

Biomedical engineering online
BACKGROUND: An efficient and accurate approach to quantify the steatosis extent of liver is important for clinical practice. For the purpose, we propose a specific designed ultrasound shear wave sequence to estimate ultrasonic and shear wave physical...

Avoidance of non-localizable obstacles in echolocating bats: A robotic model.

PLoS computational biology
Most objects and vegetation making up the habitats of echolocating bats return a multitude of overlapping echoes. Recent evidence suggests that the limited temporal and spatial resolution of bio-sonar prevents bats from separately perceiving the obje...

Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Medical hypotheses
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and hinders people's vital activities. The majority of Parkinson's patients lose their ability to speak, write and balance. Many machine learning methods...

Ultrasensitive Anti-Interference Voice Recognition by Bio-Inspired Skin-Attachable Self-Cleaning Acoustic Sensors.

ACS nano
Human voice recognition systems (VRSs) are a prerequisite for voice-controlled human-machine interfaces (HMIs). In order to avoid interference from unexpected background noises, skin-attachable VRSs are proposed to directly detect physiological mecha...

Same-day antimicrobial susceptibility test using acoustic-enhanced flow cytometry visualized with supervised machine learning.

Journal of medical microbiology
Antimicrobial susceptibility is slow to determine, taking several days to fully impact treatment. This proof-of-concept study assessed the feasibility of using machine-learning techniques for analysis of data produced by the flow cytometer-assisted ...