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Speech Recognition Software

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Crossmixed convolutional neural network for digital speech recognition.

PloS one
Digital speech recognition is a challenging problem that requires the ability to learn complex signal characteristics such as frequency, pitch, intensity, timbre, and melody, which traditional methods often face issues in recognizing. This article in...

Automated Generation of Clinical Reports Using Sensing Technologies with Deep Learning Techniques.

Sensors (Basel, Switzerland)
This study presents a pioneering approach that leverages advanced sensing technologies and data processing techniques to enhance the process of clinical documentation generation during medical consultations. By employing sophisticated sensors to capt...

Speech-based recognition and estimating severity of PTSD using machine learning.

Journal of affective disorders
BACKGROUND: Traditional methodologies for diagnosing post-traumatic stress disorder (PTSD) primarily rely on interviews, incurring considerable costs and lacking objective indices. Integrating biomarkers and machine learning techniques into this diag...

A Greek Conversational Agent for Hematologic Malignancies: Usability and User Experience Assessment.

Studies in health technology and informatics
Enabling patients to actively document their health information significantly improves understanding of how therapies work, disease progression, and overall life quality affects for those living with chronic disorders such as hematologic malignancies...

Accuracy of Speech Sound Analysis: Comparison of an Automatic Artificial Intelligence Algorithm With Clinician Assessment.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Automatic speech analysis (ASA) and automatic speech recognition systems are increasingly being used in the treatment of speech sound disorders (SSDs). When utilized as a home practice tool or in the absence of the clinician, the ASA system ...

Using articulatory feature detectors in progressive networks for multilingual low-resource phone recognitiona).

The Journal of the Acoustical Society of America
Systems inspired by progressive neural networks, transferring information from end-to-end articulatory feature detectors to similarly structured phone recognizers, are described. These networks, connecting the corresponding recurrent layers of pre-tr...

Speech recognition using an english multimodal corpus with integrated image and depth information.

Scientific reports
Traditional English corpora mainly collect information from a single modality, but lack information from multimodal information, resulting in low quality of corpus information and certain problems with recognition accuracy. To solve the above problem...

Artificial intelligence enabled smart mask for speech recognition for future hearing devices.

Scientific reports
In recent years, Lip-reading has emerged as a significant research challenge. The aim is to recognise speech by analysing Lip movements. The majority of Lip-reading technologies are based on cameras and wearable devices. However, these technologies h...

Prompt Tuning of Deep Neural Networks for Speaker-Adaptive Visual Speech Recognition.

IEEE transactions on pattern analysis and machine intelligence
Visual Speech Recognition (VSR) aims to infer speech into text depending on lip movements alone. As it focuses on visual information to model the speech, its performance is inherently sensitive to personal lip appearances and movements, and this make...