AIMC Topic: Speech

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The Impact of Attention Mechanisms on Speech Emotion Recognition.

Sensors (Basel, Switzerland)
Speech emotion recognition (SER) plays an important role in real-time applications of human-machine interaction. The Attention Mechanism is widely used to improve the performance of SER. However, the applicable rules of attention mechanism are not de...

Application of Neural Network Algorithm Based on Principal Component Image Analysis in Band Expansion of College English Listening.

Computational intelligence and neuroscience
With the development of information technology, band expansion technology is gradually applied to college English listening teaching. This technology aims to recover broadband speech signals from narrowband speech signals with a limited frequency ban...

Audio-Driven Robot Upper-Body Motion Synthesis.

IEEE transactions on cybernetics
Body language is an important aspect of human communication, which an effective human-robot interaction interface should mimic well. Human beings exchange information and convey their thoughts and feelings through gaze, facial expressions, body langu...

Environmental sound classification using temporal-frequency attention based convolutional neural network.

Scientific reports
Environmental sound classification is one of the important issues in the audio recognition field. Compared with structured sounds such as speech and music, the time-frequency structure of environmental sounds is more complicated. In order to learn ti...

Application of Deep Learning Models for Automated Identification of Parkinson's Disease: A Review (2011-2021).

Sensors (Basel, Switzerland)
Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting over 6 million people globally. Although there are symptomatic treatments that can increase the survivability of the disease, there are no curative treatments. Th...

One-dimensional convolutional neural network and hybrid deep-learning paradigm for classification of specific language impaired children using their speech.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Screening children for communicational disorders such as specific language impairment (SLI) is always challenging as it requires clinicians to follow a series of steps to evaluate the subjects. Artificial intelligence and co...

Attention-Based Joint Training of Noise Suppression and Sound Event Detection for Noise-Robust Classification.

Sensors (Basel, Switzerland)
Sound event detection (SED) recognizes the corresponding sound event of an incoming signal and estimates its temporal boundary. Although SED has been recently developed and used in various fields, achieving noise-robust SED in a real environment is t...

Localizing category-related information in speech with multi-scale analyses.

PloS one
Measurements of the physical outputs of speech-vocal tract geometry and acoustic energy-are high-dimensional, but linguistic theories posit a low-dimensional set of categories such as phonemes and phrase types. How can it be determined when and where...

Recognition of EEG Signals from Imagined Vowels Using Deep Learning Methods.

Sensors (Basel, Switzerland)
The use of imagined speech with electroencephalographic (EEG) signals is a promising field of brain-computer interfaces (BCI) that seeks communication between areas of the cerebral cortex related to language and devices or machines. However, the comp...

A High-Efficiency Fatigued Speech Feature Selection Method for Air Traffic Controllers Based on Improved Compressed Sensing.

Journal of healthcare engineering
Air traffic controller fatigue has recently received considerable attention from researchers because it is one of the main causes of air traffic incidents. Numerous research studies have been conducted to extract speech features related to fatigue, a...