AIMC Topic: Speech Perception

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Single-ended prediction of listening effort using deep neural networks.

Hearing research Dec 27, 2017
The effort required to listen to and understand noisy speech is an important factor in the evaluation of noise reduction schemes. This paper introduces a model for Listening Effort prediction from Acoustic Parameters (LEAP). The model is based on met...
Male Middle Aged Case-Control Studies Deep Learning Noise Female Aged Young Adult Adult Persons with Hearing Disabilities Speech Perception Audiometry, Speech Perceptual Masking Hearing Disorders Attention Acoustic Stimulation Auditory Pathways Hearing Models, Psychological Humans
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Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

PLoS computational biology Sep 25, 2017
There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiologic...
Female Young Adult Adult Male Models, Neurological Electroencephalography Speech Recognition Software Speech Perception Magnetoencephalography Humans Neural Networks, Computer Brain
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Hidden Markov modeling of frequency-following responses to Mandarin lexical tones.

Journal of neuroscience methods Aug 12, 2017
BACKGROUND: The frequency-following response (FFR) is a scalp-recorded electrophysiological potential reflecting phase-locked activity from neural ensembles in the auditory system. The FFR is often used to assess the robustness of subcortical pitch p...
Brain Female Young Adult Male Neuronal Plasticity Humans Machine Learning Models, Neurological Electroencephalography Markov Chains Neuropsychological Tests Speech Perception Pitch Perception
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Vowel decoding from single-trial speech-evoked electrophysiological responses: A feature-based machine learning approach.

Brain and behavior Apr 26, 2017
INTRODUCTION: Scalp-recorded electrophysiological responses to complex, periodic auditory signals reflect phase-locked activity from neural ensembles within the auditory system. These responses, referred to as frequency-following responses (FFRs), ha...
Machine Learning Female Adult Male Evoked Potentials, Auditory Humans Speech Perception Pattern Recognition, Physiological Electrophysiological Phenomena
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HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

IEEE transactions on biomedical circuits and systems Mar 1, 2017
Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and tempora...
Biometry Speech Perception Facial Recognition Humans Machine Learning Algorithms Models, Neurological Speech Recognition Software
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Perspectives on Speech Timing: Coupled Oscillator Modeling of Polish and Finnish.

Phonetica Feb 23, 2017
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...
Speech Acoustics Reaction Time Speech Perception Humans Finland Language Phonetics Poland Sampling Studies Bayes Theorem
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Statistical learning of parts and wholes: A neural network approach.

Journal of experimental psychology. General Jan 12, 2017
Statistical learning is often considered to be a means of discovering the units of perception, such as words and objects, and representing them as explicit "chunks." However, entities are not undifferentiated wholes but often contain parts that contr...
Perceptual Masking Discrimination Learning Field Dependence-Independence Paired-Associate Learning Semantics Speech Perception Space Perception Pattern Recognition, Visual Choice Behavior Neural Networks, Computer Computer Simulation Adult Bayes Theorem Humans
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Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.

Hearing research Nov 30, 2016
Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in nois...
Humans Neural Networks, Computer Algorithms Aged Aged, 80 and over Acoustic Stimulation Cochlear Implantation Electric Stimulation Speech Intelligibility Cochlear Implants Young Adult Signal Processing, Computer-Assisted Adult Persons with Hearing Disabilities Prosthesis Design Middle Aged Speech Perception Acoustics Noise Audiometry, Speech Sound Spectrography Perceptual Masking Comprehension
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Preschoolers Flexibly Adapt to Linguistic Input in a Noisy Channel.

Psychological science Nov 12, 2016
Because linguistic communication is inherently noisy and uncertain, adult language comprehenders integrate bottom-up cues from speech perception with top-down expectations about what speakers are likely to say. Further, in line with the predictions o...
Comprehension Speech Perception Environment Linguistics Psycholinguistics Child Cognition Natural Language Processing Noise Cues Reproducibility of Results Humans Communication Learning Male Female Child, Preschool
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A neural-based vocoder implementation for evaluating cochlear implant coding strategies.

Hearing research Jan 14, 2016
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and ref...
Auditory Pathways Humans Cochlear Implantation Loudness Perception Electroencephalography Neural Networks, Computer Stochastic Processes Female Psychoacoustics Signal Processing, Computer-Assisted Computer Simulation Persons with Hearing Disabilities Electric Stimulation Adult Prosthesis Design Speech Perception Cochlear Implants Male Acoustic Stimulation Speech Acoustics Middle Aged Auditory Threshold Time Factors Voice Quality
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