Two Distinct Neural Timescales for Predictive Speech Processing

The neural processing of hierarchical structure in music and speech at different timescales

Music, like speech, is a complex auditory signal that contains structures at multiple timescales, and as such is a potentially powerful entry point into the question of how the brain integrates complex streams of information. Using an experimental design modeled after previous studies that used scrambled versions of a spoken story (Lerner et al., 2011) and a silent movie (Hasson et al., 2008), ...

Neural networks for speech processing

Motor Learning Unfolds over Different Timescales in Distinct Neural Systems

Anyone who has learned how to play a musical instrument knows that translating notes on a sheet into finger movements is effortful at first, but gradually becomes more automatic over time. This widely appreciated feature of motor learning was described in 1967 by Paul Fitts and Michael Posner. In a book entitled Human Performance, the well-known psychologists proposed three stages of learning m...

Temporal Processing Neural Networks for Speech Recognition

Application of the temporal processing neural networks (TPNNs) to the speech recognition is justified by the nature of the task. Indeed ASR is a sequence recognition problem and assumes incorporation of time into decision process. Static models treat elements of sequence as independent patterns, which is clearly unrealistic. On the other hand temporal processing nets, built on the basis of mult...

Auditory Neural Processing of Speech

Recordings from single auditory neurons in response to speech and speech-like stimuli provide detailed descriptions of neural processing in the earliest stages of speech perception. These studies show that a great deal of information about both the formant pattern and voice pitch is available in both the average discharge rates and the temporal discharge patterns of auditory-nerve fibers and co...