AIMC Topic: Speech

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Crowd of Oz: A Crowd-Powered Social Robotics System for Stress Management.

Sensors (Basel, Switzerland)
Coping with stress is crucial for a healthy lifestyle. In the past, a great deal of research has been conducted to use socially assistive robots as a therapy to alleviate stress and anxiety related problems. However, building a fully autonomous socia...

Evaluating the Potential Gain of Auditory and Audiovisual Speech-Predictive Coding Using Deep Learning.

Neural computation
Sensory processing is increasingly conceived in a predictive framework in which neurons would constantly process the error signal resulting from the comparison of expected and observed stimuli. Surprisingly, few data exist on the accuracy of predicti...

Deep learning-based automated speech detection as a marker of social functioning in late-life depression.

Psychological medicine
BACKGROUND: Late-life depression (LLD) is associated with poor social functioning. However, previous research uses bias-prone self-report scales to measure social functioning and a more objective measure is lacking. We tested a novel wearable device ...

Control of speaking rate is achieved by switching between qualitatively distinct cognitive "gaits": Evidence from simulation.

Psychological review
That speakers can vary their speaking rate is evident, but how they accomplish this has hardly been studied. Consider this analogy: When walking, speed can be continuously increased, within limits, but to speed up further, humans must run. Are there ...

A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition.

Sensors (Basel, Switzerland)
Speech is the most significant mode of communication among human beings and a potential method for human-computer interaction (HCI) by using a microphone sensor. Quantifiable emotion recognition using these sensors from speech signals is an emerging ...

Two Distinct Neural Timescales for Predictive Speech Processing.

Neuron
During speech listening, the brain could use contextual predictions to optimize sensory sampling and processing. We asked if such predictive processing is organized dynamically into separate oscillatory timescales. We trained a neural network that us...

Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing.

Advanced materials (Deerfield Beach, Fla.)
Flexible piezoelectric acoustic sensors have been developed to generate multiple sound signals with high sensitivity, shifting the paradigm of future voice technologies. Speech recognition based on advanced acoustic sensors and optimized machine lear...

Companion robots for older people: importance of user-centred design demonstrated through observations and focus groups comparing preferences of older people and roboticists in South West England.

BMJ open
OBJECTIVE: Companion robots, such as Paro, may reduce agitation and depression for older people with dementia. However, contradictory research outcomes suggest robot design is not always optimal. While many researchers suggest user-centred design is ...

Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex.

PLoS computational biology
A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear ...

A comprehensive study on bilingual and multilingual speech emotion recognition using a two-pass classification scheme.

PloS one
Emotion recognition plays an important role in human-computer interaction. Previously and currently, many studies focused on speech emotion recognition using several classifiers and feature extraction methods. The majority of such studies, however, a...