AIMC Topic: Speech Recognition Software

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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...

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...

Automated speech recognition bias in personnel selection: The case of automatically scored job interviews.

The Journal of applied psychology
Organizations, researchers, and software increasingly use automatic speech recognition (ASR) to transcribe speech to text. However, ASR can be less accurate for (i.e., biased against) certain demographic subgroups. This is concerning, given that the ...

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 ...

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...

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...

Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model.

Journal of affective disorders
BACKGROUND: Prior research has associated spoken language use with depression, yet studies often involve small or non-clinical samples and face challenges in the manual transcription of speech. This paper aimed to automatically identify depression-re...

A Speech Recognition Method Based on Domain-Specific Datasets and Confidence Decision Networks.

Sensors (Basel, Switzerland)
This paper proposes a speech recognition method based on a domain-specific language speech network (DSL-Net) and a confidence decision network (CD-Net). The method involves automatically training a domain-specific dataset, using pre-trained model par...