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Speech

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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...

Toward Generalizable Machine Learning Models in Speech, Language, and Hearing Sciences: Estimating Sample Size and Reducing Overfitting.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Many studies using machine learning (ML) in speech, language, and hearing sciences rely upon cross-validations with single data splitting. This study's first purpose is to provide quantitative evidence that would incentivize researchers to i...

Decoding Single and Paired Phonemes Using 7T Functional MRI.

Brain topography
Several studies have shown that mouth movements related to the pronunciation of individual phonemes are represented in the sensorimotor cortex. This would theoretically allow for brain computer interfaces that are capable of decoding continuous speec...

Speech emotion analysis using convolutional neural network (CNN) and gamma classifier-based error correcting output codes (ECOC).

Scientific reports
Speech emotion analysis is one of the most basic requirements for the evolution of Artificial Intelligence (AI) in the field of human-machine interaction. Accurate emotion recognition in speech can be effective in applications such as online support,...

Reliability and validity of a widely-available AI tool for assessment of stress based on speech.

Scientific reports
Cigna's online stress management toolkit includes an AI-based tool that purports to evaluate a person's psychological stress level based on analysis of their speech, the Cigna StressWaves Test (CSWT). In this study, we evaluate the claim that the CSW...

Towards audio-based identification of Ethio-Semitic languages using recurrent neural network.

Scientific reports
In recent times, there is an increasing interest in employing technology to process natural language with the aim of providing information that can benefit society. Language identification refers to the process of detecting which speech a speaker app...

A Korean emotion-factor dataset for extracting emotion and factors in Korean conversations.

Scientific reports
Humans express their emotions in various ways, such as through facial expressions and voices. In particular, emotions are directly expressed or indirectly implied in the text of utterance. Research on the technology to identify emotions included in h...

Speech extraction from vibration signals based on deep learning.

PloS one
Extracting speech information from vibration response signals is a typical system identification problem, and the traditional method is too sensitive to deviations such as model parameters, noise, boundary conditions, and position. A method was propo...

Speech and language processing with deep learning for dementia diagnosis: A systematic review.

Psychiatry research
Dementia is a progressive neurodegenerative disease that burdens the person living with the disease, their families, and medical and social services. Timely diagnosis of dementia could be followed by introducing interventions that may slow down its p...

A Deep Learning Model for Correlation Analysis between Electroencephalography Signal and Speech Stimuli.

Sensors (Basel, Switzerland)
In recent years, the use of electroencephalography (EEG) has grown as a tool for diagnostic and brain function monitoring, being a simple and non-invasive method compared with other procedures like histological sampling. Typically, in order to extrac...