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Speech Acoustics

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Perspectives on Speech Timing: Coupled Oscillator Modeling of Polish and Finnish.

Phonetica
This stud y was ai med at analyzing empirical duration data for Polish spoken at different tempos using an updated version of the Coupled Oscillator Model of speech timing and rhythm variability (O'Dell and Nieminen, 1999, 2009). We use Bayesian infe...

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
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...

Estimating the spectral tilt of the glottal source from telephone speech using a deep neural network.

The Journal of the Acoustical Society of America
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...

Convolutional neural network-based automatic classification of midsagittal tongue gestural targets using B-mode ultrasound images.

The Journal of the Acoustical Society of America
Tongue gestural target classification is of great interest to researchers in the speech production field. Recently, deep convolutional neural networks (CNN) have shown superiority to standard feature extraction techniques in a variety of domains. In ...

Auditory feature representation using convolutional restricted Boltzmann machine and Teager energy operator for speech recognition.

The Journal of the Acoustical Society of America
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...

A Diadochokinesis-based expert system considering articulatory features of plosive consonants for early detection of Parkinson's disease.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: A new expert system is proposed to discriminate healthy people from people with Parkinson's Disease (PD) in early stages by using Diadochokinesis tests.

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...

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...

Detection of Pathological Voice Using Cepstrum Vectors: A Deep Learning Approach.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Computerized detection of voice disorders has attracted considerable academic and clinical interest in the hope of providing an effective screening method for voice diseases before endoscopic confirmation. This study proposes a deep-learn...

Automatic prediction of intelligible speaking rate for individuals with ALS from speech acoustic and articulatory samples.

International journal of speech-language pathology
: This research aimed to automatically predict intelligible speaking rate for individuals with Amyotrophic Lateral Sclerosis (ALS) based on speech acoustic and articulatory samples. Twelve participants with ALS and two normal subjects produced a tot...