Auditory learning induces frequency-specific plasticity in the auditory cortex. Both the auditory cortex and thalamus are involved in the cortical plasticity; however, the precise role of the intracortical circuity remains unclear until the contribut...
Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust ...
The Journal of the Acoustical Society of America
28372147
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...
The Journal of the Acoustical Society of America
28372043
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...
The Journal of the Acoustical Society of America
28618817
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...
IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
28813899
In this paper, we explore how the integration of auditory and visual cues can help teach the timing of motor skills for the purpose of motor function rehabilitation. We conducted a study using Amazon's Mechanical Turk in which 106 participants played...
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...
OBJECTIVE: Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain-machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby con...
OBJECTIVE: Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG ...
Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimized to represent features in the recent sensory pas...