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Speech

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Classification of Parkinson's disease utilizing multi-edit nearest-neighbor and ensemble learning algorithms with speech samples.

Biomedical engineering online
BACKGROUND: The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of classification in recent years. Thus, there has been an increased interest in speech pattern analysis m...

Stress Detection Using Wearable Physiological and Sociometric Sensors.

International journal of neural systems
Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detection of stress of people in a social situation by combining two sensor systems that capture physio...

Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation.

International journal of neural systems
This paper presents a neural system-based technique for segmenting short impaired speech utterances into silent, unvoiced, and voiced sections. Moreover, the proposed technique identifies those points of the (voiced) speech where the spectrum becomes...

Performing mathematics activities with non-standard units of measurement using robots controlled via speech-generating devices: three case studies.

Disability and rehabilitation. Assistive technology
Purpose To examine how using a Lego robot controlled via a speech-generating device (SGD) can contribute to how students with physical and communication impairments perform hands-on and communicative mathematics measurement activities. This study was...

Minimalistic toy robot to analyze a scenery of speaker-listener condition in autism.

Cognitive processing
Atypical neural architecture causes impairment in communication capabilities and reduces the ability of representing the referential statements of other people in children with autism. During a scenery of "speaker-listener" communication, we have ana...

Machine learning based sample extraction for automatic speech recognition using dialectal Assamese speech.

Neural networks : the official journal of the International Neural Network Society
Automatic Speaker Recognition (ASR) and related issues are continuously evolving as inseparable elements of Human Computer Interaction (HCI). With assimilation of emerging concepts like big data and Internet of Things (IoT) as extended elements of HC...

Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech.

Sensors (Basel, Switzerland)
In this paper, a new supervised classification paradigm, called classifier subset selection for stacked generalization (CSS stacking), is presented to deal with speech emotion recognition. The new approach consists of an improvement of a bi-level mul...

Deep Neural Networks with Multistate Activation Functions.

Computational intelligence and neuroscience
We propose multistate activation functions (MSAFs) for deep neural networks (DNNs). These MSAFs are new kinds of activation functions which are capable of representing more than two states, including the N-order MSAFs and the symmetrical MSAF. DNNs w...

Augmented Robotics Dialog System for Enhancing Human-Robot Interaction.

Sensors (Basel, Switzerland)
Augmented reality, augmented television and second screen are cutting edge technologies that provide end users extra and enhanced information related to certain events in real time. This enriched information helps users better understand such events,...

Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the pro...