AIMC Topic: Speech Intelligibility
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A deep learning based segregation algorithm to increase speech intelligibility for hearing-impaired listeners in reverberant-noisy conditions.
The Journal of the Acoustical Society of America
Sep 1, 2018
Recently, deep learning based speech segregation has been shown to improve human speech intelligibility in noisy environments. However, one important factor not yet considered is room reverberation, which characterizes typical daily environments. The...
Improving the performance of hearing aids in noisy environments based on deep learning technology.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
The performance of a deep-learning-based speech enhancement (SE) technology for hearing aid users, called a deep denoising autoencoder (DDAE), was investigated. The hearing-aid speech perception index (HASPI) and the hearing- aid sound quality index ...
Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality.
Trends in hearing
Jan 1, 2018
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...
Joint Dictionary Learning-Based Non-Negative Matrix Factorization for Voice Conversion to Improve Speech Intelligibility After Oral Surgery.
IEEE transactions on bio-medical engineering
Nov 1, 2017
This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patie...
An algorithm to increase intelligibility for hearing-impaired listeners in the presence of a competing talker.
The Journal of the Acoustical Society of America
Jun 1, 2017
Individuals with hearing impairment have particular difficulty perceptually segregating concurrent voices and understanding a talker in the presence of a competing voice. In contrast, individuals with normal hearing perform this task quite well. This...
Audiometry, Speech
Perceptual Masking
Speech Perception
Auditory Threshold
Hearing Loss, Sensorineural
Signal Processing, Computer-Assisted
Correction of Hearing Impairment
Signal-To-Noise Ratio
Comprehension
Acoustic Stimulation
Young Adult
Hearing
Humans
Male
Speech Intelligibility
Female
Middle Aged
Hearing Aids
Aged
Deep Learning
Persons with Hearing Disabilities
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...
Speech Intelligibility
Speech Acoustics
Laryngectomy
Transducers
Lip
Voice Quality
Larynx, Artificial
Tongue
Magnets
Magnetic Fields
Magnetics
Signal Processing, Computer-Assisted
Prosthesis Design
Acoustics
Humans
Sound Spectrography
Machine Learning
Biomechanical Phenomena
Time Factors
Recovery of Function
Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners.
The Journal of the Acoustical Society of America
Mar 1, 2017
Machine-learning based approaches to speech enhancement have recently shown great promise for improving speech intelligibility for hearing-impaired listeners. Here, the performance of three machine-learning algorithms and one classical algorithm, Wie...
Humans
Acoustic Stimulation
Electric Stimulation
Speech Intelligibility
Hearing Aids
Perceptual Masking
Speech Perception
Recognition, Psychology
Audiometry, Speech
Male
Hearing Loss
Middle Aged
Persons with Hearing Disabilities
Neural Networks, Computer
Noise
Machine Learning
Signal Processing, Computer-Assisted
Female
Aged
Improving quality and intelligibility of speech using single microphone for the broadband fMRI noise at low SNR.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the p...
Difficulty understanding speech in noise by the hearing impaired: underlying causes and technological solutions.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
A primary complaint of hearing-impaired individuals involves poor speech understanding when background noise is present. Hearing aids and cochlear implants often allow good speech understanding in quiet backgrounds. But hearing-impaired individuals a...
Intelligent hearing aids: the next revolution.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
The first revolution in hearing aids came from nonlinear amplification, which allows better compensation for both soft and loud sounds. The second revolution stemmed from the introduction of digital signal processing, which allows better programmabil...
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