AIMC Topic: Acoustics

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Active learning for bird sound classification via a kernel-based extreme learning machine.

The Journal of the Acoustical Society of America Oct 1, 2017
In recent years, research fields, including ecology, bioacoustics, signal processing, and machine learning, have made bird sound recognition a part of their focus. This has led to significant advancements within the field of ornithology, such as impr...
Databases, Factual Animals Supervised Machine Learning Acoustics Pattern Recognition, Automated Vocalization, Animal Birds Support Vector Machine Signal Processing, Computer-Assisted
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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 ...
Porosity Signal Processing, Computer-Assisted Acoustics Neural Networks, Computer Time Factors Automobiles Pattern Recognition, Automated Hydrocarbons Surface Properties Motion Sound Sound Spectrography Pressure Fourier Analysis Transducers, Pressure Friction Noise, Transportation
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Auditory feature representation using convolutional restricted Boltzmann machine and Teager energy operator for speech recognition.

The Journal of the Acoustical Society of America Jun 1, 2017
In this letter, authors propose an auditory feature representation technique with the filterbank learned using an annealing dropout convolutional restricted Boltzmann machine (ConvRBM) and noise-robust energy estimation using the Teager energy operat...
Voice Quality Pattern Recognition, Automated Speech Acoustics Speech Production Measurement Neural Networks, Computer Signal Processing, Computer-Assisted Humans Machine Learning Acoustics Time Factors Sound Spectrography
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Estimating the spectral tilt of the glottal source from telephone speech using a deep neural network.

The Journal of the Acoustical Society of America Apr 1, 2017
Estimation of the spectral tilt of the glottal source has several applications in speech analysis and modification. However, direct estimation of the tilt from telephone speech is challenging due to vocal tract resonances and distortion caused by spe...
Speech Acoustics Speech Production Measurement Phonation Telephone Voice Quality Glottis Signal Processing, Computer-Assisted Acoustics Sound Spectrography Female Male Deep Learning Humans
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Predicting the perception of performed dynamics in music audio with ensemble learning.

The Journal of the Acoustical Society of America Mar 1, 2017
By varying the dynamics in a musical performance, the musician can convey structure and different expressions. Spectral properties of most musical instruments change in a complex way with the performed dynamics, but dedicated audio features for model...
Time Perception Signal Processing, Computer-Assisted Acoustics Humans Loudness Perception Machine Learning Computer Simulation Sound Spectrography Pitch Perception Acoustic Stimulation Reproducibility of Results Models, Psychological Time Factors Music Judgment Periodicity Auditory Perception
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Restoring speech following total removal of the larynx by a learned transformation from sensor data to acoustics.

The Journal of the Acoustical Society of America Mar 1, 2017
Total removal of the larynx may be required to treat laryngeal cancer: speech is lost. This article shows that it may be possible to restore speech by sensing movement of the remaining speech articulators and use machine learning algorithms to derive...
Time Factors Recovery of Function Humans Signal Processing, Computer-Assisted Laryngectomy Machine Learning Prosthesis Design Magnetics Voice Quality Biomechanical Phenomena Transducers Acoustics Speech Intelligibility Tongue Larynx, Artificial Lip Sound Spectrography Speech Acoustics Magnets Magnetic Fields
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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...
Time Factors Equipment Failure Motion Equipment Failure Analysis Models, Theoretical Bayes Theorem Sound Support Vector Machine Acoustics Materials Testing
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