Due to the difficulties and complications in the quantitative assessment of traumatic brain
injury (TBI) and its increasing relevance in today's world, robust detection of TBI has become …

Naturalistic speech recordings usually contain speech signals from multiple speakers. This
phenomenon can degrade the performance of speech technologies due to the complexity of …

Training acoustic models with sequentially incoming data-while both leveraging new data
and avoiding the forgetting effect-is an essential obstacle to achieving human intelligence …

Speech coding facilitates the transmission of speech over low-bandwidth networks with
minimal distortion. Neural-network based speech codecs have recently demonstrated …

In this paper, we demonstrate the significance of restoring harmonics of the fundamental
frequency (pitch) in the deep neural network (DNN)-based speech enhancement. The …

With the advancement of NB-IoT, the demand for speech communication has surged in
applications such as medical assistance, smart alarms, and smart homes. Consequently …

The disclosure includes using dilation of speech content from a separated audio input for
speech recognition. An audio input from a speaker and predicted changes for the audio …

This thesis proposes a new, fully convolutional neural network architecture for frame-wise
automatic chord recognition and, by doing so, expands the deep learning vocabulary of the …

Voice control is a major growing feature that changes the way people are living their lives.
Since speech recognition and natural language processing continues to advance at a rapid …