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Speech

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Improvement of Speech Recognition Technology in Piano Music Scene Based on Deep Learning of Internet of Things.

Computational intelligence and neuroscience
The main goal of speech recognition technology is to use computers to convert human analog speech signals into computer-generated signals, such as behavior patterns or binary codes. Different from speaker identification and speaker confirmation, the ...

Deep Learning Models for Fast Retrieval and Extraction of French Speech Vocabulary Applications.

Computational intelligence and neuroscience
Due to the large French vocabulary, how quickly retrieve and accurately identify the required vocabulary is still a big challenge in French learning. In view of the above problems, we introduce a deep learning algorithm in this study to upgrade and o...

Research on Chinese Speech Emotion Recognition Based on Deep Neural Network and Acoustic Features.

Sensors (Basel, Switzerland)
In recent years, the use of Artificial Intelligence for emotion recognition has attracted much attention. The industrial applicability of emotion recognition is quite comprehensive and has good development potential. This research uses voice emotion ...

Arabic Speech Analysis for Classification and Prediction of Mental Illness due to Depression Using Deep Learning.

Computational intelligence and neuroscience
Depression is a global prevalent ailment for possible mental illness or mental disorder globally. Recognizing depressed early signs is critical for evaluating and preventing mental illness. With the progress of machine learning, it is possible to mak...

A Deep Learning Approach for Quantifying Vocal Fold Dynamics During Connected Speech Using Laryngeal High-Speed Videoendoscopy.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Voice disorders are best assessed by examining vocal fold dynamics in connected speech. This can be achieved using flexible laryngeal high-speed videoendoscopy (HSV), which enables us to study vocal fold mechanics with high temporal details....

A Bimodal Deep Learning Architecture for EEG-fNIRS Decoding of Overt and Imagined Speech.

IEEE transactions on bio-medical engineering
OBJECTIVE: Brain-computer interfaces (BCI) studies are increasingly leveraging different attributes of multiple signal modalities simultaneously. Bimodal data acquisition protocols combining the temporal resolution of electroencephalography (EEG) wit...

Automatic Speech Recognition Method Based on Deep Learning Approaches for Uzbek Language.

Sensors (Basel, Switzerland)
Communication has been an important aspect of human life, civilization, and globalization for thousands of years. Biometric analysis, education, security, healthcare, and smart cities are only a few examples of speech recognition applications. Most s...

End-to-End Sentence-Level Multi-View Lipreading Architecture with Spatial Attention Module Integrated Multiple CNNs and Cascaded Local Self-Attention-CTC.

Sensors (Basel, Switzerland)
Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in re...

Automated Dysarthria Severity Classification: A Study on Acoustic Features and Deep Learning Techniques.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Assessing the severity level of dysarthria can provide an insight into the patient's improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech recognition systems. In this article, we present a comparative study on the cla...

Robot touch with speech boosts positive emotions.

Scientific reports
A gentle touch is an essential part of human interaction that produces a positive care effect. Previously, robotics studies have shown that robots can reproduce a gentle touch that elicits similar, positive emotional responses in humans. However, whe...