AIMC Topic: Speech

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Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate interpretation of human intentions for both efficiency and safety. Electroencephalogram (EEG) signals, commonly employed to measure brain activity, off...

EEG based depression detection by machine learning: Does inner or overt speech condition provide better biomarkers when using emotion words as experimental cues?

Journal of psychiatric research
BACKGROUND: Objective diagnostic approaches need to be tested to enhance the efficacy of depression detection. Non-invasive EEG-based identification represents a promising area.

Speech and language patterns in autism: Towards natural language processing as a research and clinical tool.

Psychiatry research
Speech and language differences have long been described as important characteristics of autism spectrum disorder (ASD). Linguistic abnormalities range from prosodic differences in pitch, intensity, and rate of speech, to language idiosyncrasies and ...

Cross-lingual hate speech detection using domain-specific word embeddings.

PloS one
THIS ARTICLE USES WORDS OR LANGUAGE THAT IS CONSIDERED PROFANE, VULGAR, OR OFFENSIVE BY SOME READERS. Hate speech detection in online social networks is a multidimensional problem, dependent on language and cultural factors. Most supervised learning ...

Code-mixing unveiled: Enhancing the hate speech detection in Arabic dialect tweets using machine learning models.

PloS one
Technological developments over the past few decades have changed the way people communicate, with platforms like social media and blogs becoming vital channels for international conversation. Even though hate speech is vigorously suppressed on socia...

The Collaboverse: A Collaborative Data-Sharing and Speech Analysis Platform.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Collaboration in the field of speech-language pathology occurs across a variety of digital devices and can entail the usage of multiple software tools, systems, file formats, and even programming languages. Unfortunately, gaps between the la...

Speech decoding from stereo-electroencephalography (sEEG) signals using advanced deep learning methods.

Journal of neural engineering
Brain-computer interfaces (BCIs) are technologies that bypass damaged or disrupted neural pathways and directly decode brain signals to perform intended actions. BCIs for speech have the potential to restore communication by decoding the intended spe...

Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Identification of individuals with mild cognitive impairment (MCI) who are at risk of developing Alzheimer's disease (AD) is crucial for early intervention and selection of clinical trials.

Spectro-temporal acoustical markers differentiate speech from song across cultures.

Nature communications
Humans produce two forms of cognitively complex vocalizations: speech and song. It is debated whether these differ based primarily on culturally specific, learned features, or if acoustical features can reliably distinguish them. We study the spectro...

Emotion recognition for human-computer interaction using high-level descriptors.

Scientific reports
Recent research has focused extensively on employing Deep Learning (DL) techniques, particularly Convolutional Neural Networks (CNN), for Speech Emotion Recognition (SER). This study addresses the burgeoning interest in leveraging DL for SER, specifi...