AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Phonetics

Showing 21 to 30 of 36 articles

Clear Filters

A transfer learning approach to goodness of pronunciation based automatic mispronunciation detection.

The Journal of the Acoustical Society of America
Goodness of pronunciation (GOP) is the most widely used method for automatic mispronunciation detection. In this paper, a transfer learning approach to GOP based mispronunciation detection when applying maximum F1-score criterion (MFC) training to de...

Evaluating automatic speech recognition systems as quantitative models of cross-lingual phonetic category perception.

The Journal of the Acoustical Society of America
Theories of cross-linguistic phonetic category perception posit that listeners perceive foreign sounds by mapping them onto their native phonetic categories, but, until now, no way to effectively implement this mapping has been proposed. In this pape...

Encoding of Articulatory Kinematic Trajectories in Human Speech Sensorimotor Cortex.

Neuron
When speaking, we dynamically coordinate movements of our jaw, tongue, lips, and larynx. To investigate the neural mechanisms underlying articulation, we used direct cortical recordings from human sensorimotor cortex while participants spoke natural ...

Learning mechanisms in cue reweighting.

Cognition
Feedback has been shown to be effective in shifting attention across perceptual cues to a phonological contrast in speech perception (Francis, Baldwin & Nusbaum, 2000). However, the learning mechanisms behind this process remain obscure. We compare t...

Cimind: A phonetic-based tool for multilingual named entity recognition in biomedical texts.

Journal of biomedical informatics
BACKGROUND: Extracting concepts from biomedical texts is a key to support many advanced applications such as biomedical information retrieval. However, in clinical notes Named Entity Recognition (NER) has to deal with various types of errors such as ...

Semi-supervised learning of a nonnative phonetic contrast: How much feedback is enough?

Attention, perception & psychophysics
Semi-supervised learning refers to learning that occurs when feedback about performance is provided on only a subset of training trials. Algorithms for semi-supervised learning are popular in machine learning because of their minimal reliance on labe...

Combining string and phonetic similarity matching to identify misspelt names of drugs in medical records written in Portuguese.

Journal of biomedical semantics
BACKGROUND: There is an increasing amount of unstructured medical data that can be analysed for different purposes. However, information extraction from free text data may be particularly inefficient in the presence of spelling errors. Existing appro...

Improving clinical named entity recognition in Chinese using the graphical and phonetic feature.

BMC medical informatics and decision making
BACKGROUND: Clinical Named Entity Recognition is to find the name of diseases, body parts and other related terms from the given text. Because Chinese language is quite different with English language, the machine cannot simply get the graphical and ...

Complexity Measures of Voice Recordings as a Discriminative Tool for Parkinson's Disease.

Biosensors
In this paper, we have investigated the differences in the voices of Parkinson's disease (PD) and age-matched control (CO) subjects when uttering three phonemes using two complexity measures: fractal dimension (FD) and normalised mutual information (...

Density and Distinctiveness in Early Word Learning: Evidence From Neural Network Simulations.

Cognitive science
High phonological neighborhood density has been associated with both advantages and disadvantages in early word learning. High density may support the formation and fine-tuning of new word sound memories-a process termed lexical configuration (e.g., ...