AI Medical Compendium Journal:
The Journal of the Acoustical Society of America

Showing 61 to 70 of 100 articles

A talker-independent deep learning algorithm to increase intelligibility for hearing-impaired listeners in reverberant competing talker conditions.

The Journal of the Acoustical Society of America
Deep learning based speech separation or noise reduction needs to generalize to voices not encountered during training and to operate under multiple corruptions. The current study provides such a demonstration for hearing-impaired (HI) listeners. Sen...

A feedforward neural network for direction-of-arrival estimation.

The Journal of the Acoustical Society of America
This paper examines the relationship between conventional beamforming and linear supervised learning, then develops a nonlinear deep feed-forward neural network (FNN) for direction-of-arrival (DOA) estimation. First, conventional beamforming is refor...

Beluga whale acoustic signal classification using deep learning neural network models.

The Journal of the Acoustical Society of America
Over a decade after the Cook Inlet beluga (Delphinapterus leucas) was listed as endangered in 2008, the population has shown no sign of recovery. Lack of ecological knowledge limits the understanding of, and ability to manage, potential threats imped...

Convolutional neural network for single-sensor acoustic localization of a transiting broadband source in very shallow water.

The Journal of the Acoustical Society of America
When a broadband source of radiated noise transits past a fixed hydrophone, a Lloyd's mirror constructive/destructive interference pattern can be observed in the output spectrogram. By taking the spectrum of a (log) spectrum, the power cepstrum detec...

Deep learning classification for improved bicoherence feature based on cyclic modulation and cross-correlation.

The Journal of the Acoustical Society of America
This paper aims to present an improved bicoherence spectrum (IBS) combined with cyclic modulation spectrum (CMS) and cross-correlation that is suitable for classification of hydrophone signals involving deep learning (DL). First, the proposed feature...

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-...

General audio tagging with ensembling convolutional neural networks and statistical features.

The Journal of the Acoustical Society of America
Audio tagging aims to infer descriptive labels from audio clips and it is challenging due to the limited size of data and noisy labels. The solution to the tagging task is described in this paper. The main contributions include the following: an ense...

Differentiating post-cancer from healthy tongue muscle coordination patterns during speech using deep learning.

The Journal of the Acoustical Society of America
The ability to differentiate post-cancer from healthy tongue muscle coordination patterns is necessary for the advancement of speech motor control theories and for the development of therapeutic and rehabilitative strategies. A deep learning approach...

Development of an automatic classifier for the prediction of hearing impairment from industrial noise exposure.

The Journal of the Acoustical Society of America
The ISO-1999 [(2013). International Organization for Standardization, Geneva, Switzerland] standard is the most commonly used approach for estimating noise-induced hearing trauma. However, its insensitivity to noise characteristics limits its practic...