AIMC Topic: Sound Spectrography
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Tensorial dynamic time warping with articulation index representation for efficient audio-template learning.
The Journal of the Acoustical Society of America
Mar 1, 2018
Audio classification techniques often depend on the availability of a large labeled training dataset for successful performance. However, in many application domains of audio classification (e.g., wildlife monitoring), obtaining labeled data is still...
Detection of ground parrot vocalisation: A multiple instance learning approach.
The Journal of the Acoustical Society of America
Sep 1, 2017
Ground parrot vocalisation can be considered as an audio event. Test-based diverse density multiple instance learning (TB-DD-MIL) is proposed for detecting this event in audio files recorded in the field. The proposed method is motivated by the advan...
Unsupervised modulation filter learning for noise-robust speech recognition.
The Journal of the Acoustical Society of America
Sep 1, 2017
The modulation filtering approach to robust automatic speech recognition (ASR) is based on enhancing perceptually relevant regions of the modulation spectrum while suppressing the regions susceptible to noise. In this paper, a data-driven unsupervise...
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 ...
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...
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...
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...
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...
Humans
Machine Learning
Biomechanical Phenomena
Time Factors
Recovery of Function
Signal Processing, Computer-Assisted
Speech Acoustics
Laryngectomy
Transducers
Lip
Magnets
Prosthesis Design
Magnetic Fields
Voice Quality
Acoustics
Magnetics
Larynx, Artificial
Sound Spectrography
Speech Intelligibility
Tongue
Speaker-dependent multipitch tracking using deep neural networks.
The Journal of the Acoustical Society of America
Feb 1, 2017
Multipitch tracking is important for speech and signal processing. However, it is challenging to design an algorithm that achieves accurate pitch estimation and correct speaker assignment at the same time. In this paper, deep neural networks (DNNs) a...
Automatic Wheezing Detection Based on Signal Processing of Spectrogram and Back-Propagation Neural Network.
Journal of healthcare engineering
Jan 1, 2015
Wheezing is a common clinical symptom in patients with obstructive pulmonary diseases such as asthma. Automatic wheezing detection offers an objective and accurate means for identifying wheezing lung sounds, helping physicians in the diagnosis, long-...
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