AIMC Topic: Speech Perception

Clear Filters Showing 1 to 10 of 122 articles

Testing Sentence-in-Noise Recognition With Synthetic Speech and Automatic Speech Recognition.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Characterizing speech-in-noise recognition is fundamental to both clinical audiology and hearing research. Current methods rely on human speech recordings and human testers. However, modern artificial intelligence tools could automate both s...

Breaking down the ear-brain dichotomy: the effects of age-related hearing loss on the cortical language system.

NeuroImage
Older individuals frequently experience hearing difficulties, often due to sensorineural hearing loss (HL) primarily originating in the inner ear. However, it is not uncommon for older adults with HL to also exhibit impairments in speech intelligibil...

CIRE: A Chinese EEG Dataset for decoding speech intention modulated by prosodic emotion.

Scientific data
Neural decoding of speech intention could advance the development and application of brain-computer interface (BCI) technology. Currently, lack of dataset limited the research on decoding the true speech intention, especially the diverse intentions e...

Hierarchical dynamic coding coordinates speech comprehension in the human brain.

Proceedings of the National Academy of Sciences of the United States of America
Speech comprehension involves transforming an acoustic waveform into meaning. To do so, the human brain generates a hierarchy of features that converts the sensory input into increasingly abstract language properties. However, little is known about h...

Wordsworth: A generative word dataset for comparison of speech representations in humans and neural networks.

Scientific data
Speech perception is fundamental for human communication, but its neural basis is not well understood. Furthermore, while modern neural networks (NNs) can accurately recognize speech, whether they effectively model human speech processing remains unc...

Research on optimal deep learning modeling in HaiNan dialect recognition.

Scientific reports
The speech recognition task of the HaiNan dialect faces significant differences in phonology, intonation, and grammatical structure among dialects, which in turn show significant regionalization characteristics, which makes the task of dialect-to-Man...

Single-microphone deep envelope separation based auditory attention decoding for competing speech and music.

Journal of neural engineering
In this study, we introduce an end-to-end single microphone deep learning system for source separation and auditory attention decoding (AAD) in a competing speech and music setup. Deep source separation is applied directly on the envelope of the obse...

Automatic development of speech-in-noise hearing tests using machine learning.

Scientific reports
Understanding speech in noisy environments is a primary challenge for individuals with hearing loss, affecting daily communication and quality of life. Traditional speech-in-noise tests are essential for screening and diagnosing hearing loss but are ...

Natural language processing models reveal neural dynamics of human conversation.

Nature communications
Through conversation, humans engage in a complex process of alternating speech production and comprehension to communicate. The neural mechanisms that underlie these complementary processes through which information is precisely conveyed by language,...

Machine Learning Feasibility in Cochlear Implant Speech Perception Outcomes-Moving Beyond Single Biomarkers for Cochlear Implant Performance Prediction.

Ear and hearing
OBJECTIVES: Machine learning (ML) is an emerging discipline centered around complex pattern matching and large data-based prediction modeling and can improve precision medicine healthcare. Cochlear implants (CI) are highly effective, however, outcome...