AIMC Topic: Sound

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Improving the performance of hearing aids in noisy environments based on deep learning technology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
The performance of a deep-learning-based speech enhancement (SE) technology for hearing aid users, called a deep denoising autoencoder (DDAE), was investigated. The hearing-aid speech perception index (HASPI) and the hearing- aid sound quality index ...
Hearing Loss, Sensorineural Auditory Perception Speech Intelligibility Hearing Aids Speech Perception Hearing Tests Deep Learning Sound Humans
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Convolutional Feature Vectors and Support Vector Machine for Animal Sound Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Pattern classification based on deep network outperforms conventional methods in many tasks. However, if the database for training exhibits internal representation that lacks substantial discernibility for different classes, the network is considered...
Neural Networks, Computer Databases, Factual Sound Animals Support Vector Machine
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Crackle and Breathing Phase Detection in Lung Sounds with Deep Bidirectional Gated Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
In this paper, we present a method for event detection in single-channel lung sound recordings. This includes the detection of crackles and breathing phase events (inspiration/expiration). Therefore, we propose an event detection approach with spectr...
Humans Respiration Respiratory Sounds Sound Heart Sounds Neural Networks, Computer Sound Spectrography Lung
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Classification of producer characteristics in primate long calls using neural networks.

The Journal of the Acoustical Society of America Jul 1, 2018
Primate long calls are high-amplitude vocalizations that can be critical in maintaining intragroup contact and intergroup spacing, and can encode abundant information about a call's producer, such as age, sex, and individual identity. Long calls of t...
Animals Sound Neural Networks, Computer Female Nerve Net Humans Saguinus Vocalization, Animal Behavior, Animal
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Automatic fish sounds classification.

The Journal of the Acoustical Society of America May 1, 2018
The work presented in this paper focuses on the use of acoustic systems for passive acoustic monitoring of ocean vitality for fish populations. Specifically, it focuses on the use of acoustic systems for passive acoustic monitoring of ocean vitality ...
Vocalization, Animal Animals Acoustics Machine Learning Sound Fishes
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Pavement type and wear condition classification from tire cavity acoustic measurements with artificial neural networks.

The Journal of the Acoustical Society of America Jun 1, 2017
Tire road noise is the major contributor to traffic noise, which leads to general annoyance, speech interference, and sleep disturbances. Standardized methods to measure tire road noise are expensive, sophisticated to use, and they cannot be applied ...
Hydrocarbons Surface Properties Pressure Fourier Analysis Noise, Transportation Sound Spectrography Neural Networks, Computer Pattern Recognition, Automated Time Factors Friction Motion Signal Processing, Computer-Assisted Transducers, Pressure Sound Acoustics Automobiles Porosity
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Reliable bearing fault diagnosis using Bayesian inference-based multi-class support vector machines.

The Journal of the Acoustical Society of America Feb 1, 2017
This letter presents a multi-fault diagnosis scheme for bearings using hybrid features extracted from their acoustic emissions and a Bayesian inference-based one-against-all support vector machine (Bayesian OAASVM) for multi-class classification. The...
Materials Testing Bayes Theorem Equipment Failure Analysis Support Vector Machine Acoustics Motion Time Factors Equipment Failure Sound Models, Theoretical
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