AIMC Topic: Acoustics

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Detection of early reflections from a binaural activity map using neural networks.

The Journal of the Acoustical Society of America
Human listeners localize sounds to their sources despite competing directional cues from early room reflections. Binaural activity maps computed from a running signal can provide useful information about the presence of room reflections, but must be ...

Sound source ranging using a feed-forward neural network trained with fitting-based early stopping.

The Journal of the Acoustical Society of America
When a feed-forward neural network (FNN) is trained for acoustic source ranging in an ocean waveguide, it is difficult evaluating the FNN ranging accuracy of unlabeled test data. The label is the distance between source and receiver array. A fitting-...

Automated Placenta Segmentation with a Convolutional Neural Network Weighted by Acoustic Shadow Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Placental assessment through routine obstetrical ultrasound is often limited to documenting its location and ruling out placenta previa. However, many obstetrical complications originate from abnormal focal or global placental development. Technical ...

A Convolutional Neural Network for 250-MHz Quantitative Acoustic-microscopy Resolution Enhancement.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Quantitative acoustic microscopy (QAM) permits the formation of quantitative two-dimensional (2D) maps of acoustic and mechanical properties of soft tissues at microscopic resolution. The 2D maps formed using our custom SAM systems employing a 250-MH...

Snoring - An Acoustic Definition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Objective- The distinction of snoring and loud breathing is often subjective and lies in the ear of the beholder. The aim of this study is to identify and assess acoustic features with a high suitability to distinguish these two classes of sound, in ...

A Comparative Study of Features for Acoustic Cough Detection Using Deep Architectures.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic cough detection is key to tracking the condition of patients suffering from tuberculosis. We evaluate various acoustic features for performing cough detection using deep architectures. As most previous studies have adopted features designed...

Deep learning models to remix music for cochlear implant users.

The Journal of the Acoustical Society of America
The severe hearing loss problems that some people suffer can be treated by providing them with a surgically implanted electrical device called cochlear implant (CI). CI users struggle to perceive complex audio signals such as music; however, previous...

Automatic fish sounds classification.

The Journal of the Acoustical Society of America
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 ...

Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality.

Trends in hearing
Despite great advances in hearing-aid technology, users still experience problems with noise in windy environments. The potential benefits of using a deep recurrent neural network (RNN) for reducing wind noise were assessed. The RNN was trained using...

A transfer learning approach to goodness of pronunciation based automatic mispronunciation detection.

The Journal of the Acoustical Society of America
Goodness of pronunciation (GOP) is the most widely used method for automatic mispronunciation detection. In this paper, a transfer learning approach to GOP based mispronunciation detection when applying maximum F1-score criterion (MFC) training to de...