AIMC Topic: Speech

Clear Filters Showing 201 to 210 of 395 articles

Gender Identification in a Two-Level Hierarchical Speech Emotion Recognition System for an Italian Social Robot.

Sensors (Basel, Switzerland)
The real challenge in Human-Robot Interaction (HRI) is to build machines capable of perceiving human emotions so that robots can interact with humans in a proper manner. Emotion varies accordingly to many factors, and gender represents one of the mos...

Hybrid machine learning classification scheme for speaker identification.

Journal of forensic sciences
Motivated by the requirement to prepare for the next generation of "Automatic Spokesperson Recognition" (ASR) system, this paper applied the fused spectral features with hybrid machine learning (ML) strategy to the speech communication field. This st...

Deploying Machine Learning Techniques for Human Emotion Detection.

Computational intelligence and neuroscience
Emotion recognition is one of the trending research fields. It is involved in several applications. Its most interesting applications include robotic vision and interactive robotic communication. Human emotions can be detected using both speech and v...

Robot System Assistant (RoSA): Towards Intuitive Multi-Modal and Multi-Device Human-Robot Interaction.

Sensors (Basel, Switzerland)
This paper presents an implementation of RoSA, a Robot System Assistant, for safe and intuitive human-machine interaction. The interaction modalities were chosen and previously reviewed using a Wizard of Oz study emphasizing a strong propensity for s...

Metaheuristics with Deep Learning-Enabled Parkinson's Disease Diagnosis and Classification Model.

Journal of healthcare engineering
Parkinson's disease (PD) affects the movement of people, including the differences in writing skill, speech, tremor, and stiffness in muscles. It is significant to detect the PD at the initial stages so that the person can live a peaceful life for a ...

Improving Speech Emotion Recognition With Adversarial Data Augmentation Network.

IEEE transactions on neural networks and learning systems
When training data are scarce, it is challenging to train a deep neural network without causing the overfitting problem. For overcoming this challenge, this article proposes a new data augmentation network-namely adversarial data augmentation network...

Natural Language Processing markers in first episode psychosis and people at clinical high-risk.

Translational psychiatry
Recent work has suggested that disorganised speech might be a powerful predictor of later psychotic illness in clinical high risk subjects. To that end, several automated measures to quantify disorganisation of transcribed speech have been proposed. ...

Generalisation Gap of Keyword Spotters in a Cross-Speaker Low-Resource Scenario.

Sensors (Basel, Switzerland)
Models for keyword spotting in continuous recordings can significantly improve the experience of navigating vast libraries of audio recordings. In this paper, we describe the development of such a keyword spotting system detecting regions of interest...

Presentation Attack Detection on Limited-Resource Devices Using Deep Neural Classifiers Trained on Consistent Spectrogram Fragments.

Sensors (Basel, Switzerland)
The presented paper is concerned with detection of presentation attacks against unsupervised remote biometric speaker verification, using a well-known challenge-response scheme. We propose a novel approach to convolutional phoneme classifier training...

Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning.

Sensors (Basel, Switzerland)
Emotion Recognition is attracting the attention of the research community due to the multiple areas where it can be applied, such as in healthcare or in road safety systems. In this paper, we propose a multimodal emotion recognition system that relie...