Automatic visual word recognition

The purpose of the current study was to examine the combined effect of word length and lexical frequency in a lexical decision task in second- and fifth-grade children with varying language skills. The participants, 47 second graders and 55 fifth graders, performed a lexical decision task in which word length and lexical frequency were manipulated orthogonally so that 32 words were short and frequent (e.g., fleur [flower]), 32 words were short and rare (e.g., navet [turnip]), 32 words were long and frequent (e...

This paper addresses the problem of feature encoding for gait analysis using multimodal time series sensory data. In recent years, the dramatic increase in the use of numerous sensors, e.g., inertial measurement unit (IMU), in our daily wearable devices has gained the interest of the research community to collect kinematic and kinetic data to analyze the gait. The most crucial step for gait analysis is to find the set of appropriate features from continuous time series data to accurately represent human locomotion...

Automatic Speech Recognition (ASR) is a technology that converts spoken words into text, facilitating interaction between humans and machines. One of the most common applications of ASR is Speech-To-Text (STT) technology, which simplifies user workflows by transcribing spoken words into text. In the medical field, STT has the potential to significantly reduce the workload of clinicians who rely on typists to transcribe their voice recordings. However, developing an STT model for the medical domain is challenging due to the lack of sufficient speech and text datasets...

BACKGROUND: Automatic speech recognition (ASR) technology is increasingly being used for transcription in clinical contexts. Although there are numerous transcription services using ASR, few studies have compared the word error rate (WER) between different transcription services among different diagnostic groups in a mental health setting. There has also been little research into the types of words ASR transcriptions mistakenly generate or omit. OBJECTIVE: This study compared the WER of 3 ASR transcription services (Amazon Transcribe [Amazon...

Discrimination of reversible mirrored letters (e.g., d and b) poses a challenge when learning to read as it requires overcoming mirror invariance, an evolutionary-old perceptual tendency of processing mirror images as equivalent. The present study investigated when, in reading development, mirror-image discrimination becomes automatic during visual word recognition. The developmental trajectory of masked priming effects was investigated from 2nd to 6th grade and in adults, by manipulating letter type (nonreversible; reversible) and prime condition (control; identity; mirrored; rotated)...

BACKGROUND: Breast cancer is a major cause of mortality among women worldwide. Dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI) is a good imaging technique that can show temporal information about the kinetics of the contrast agent in suspicious breast lesions as well as acceptable spatial resolution. Computer-aided detection systems assist in the detection of lesions through medical image processing techniques combined with computerized analysis and calculation, which in turn helps radiologists recognize molecular subtypes of breast lesions that will be beneficial for better treatment plan decisions...

Morphologically complex words are common across different languages, especially in Chinese, because more than 90% of common modern Chinese words are complex words. Many behavioral studies have suggested the whole-word processing of Chinese complex words, but the neural correlates of whole-word processing remain unclear. Previous electrophysiological studies revealed automatic and early (∼250 ms) access to the orthographic forms of monomorphic words in the ventral occipitotemporal area. In this study, we investigated whether there is also automatic and early orthographic recognition of Chinese complex words (as whole units) by recording event-related potentials (ERPs)...

OBJECTIVES: Everyday listening environments are filled with competing noise and distractors. Although significant research has examined the effect of competing noise on speech recognition and listening effort, little is understood about the effect of distraction. The framework for understanding effortful listening recognizes the importance of attention-related processes in speech recognition and listening effort; however, it underspecifies the role that they play, particularly with respect to distraction...

The task being undertaken can influence orthographic, phonological and semantic processes. In linguistic research, two tasks are most often used: a task requiring a decision in relation to the presented word and a passive reading task which does not require a decision regarding the presented word. The results of studies using these different tasks are not always consistent. This study aimed to explore brain responses associated with the process of recognition of spelling errors, as well as the influence of the task on this process...

INTRODUCTION: Across multiples languages, research demonstrates the important relationship between reading fluency and comprehension. Put simply, a fluent reader has greater attention and memory resources to use higher-order functions in reading, resulting in better comprehension of text. Some reading fluency interventions have shown positive results in improving students' text reading fluency and comprehension; however, this research has predominantly been conducted with English-speaking students...

Food recognition and weight estimation based on image methods have always been hotspots in the field of computer vision and medical nutrition, and have good application prospects in digital nutrition therapy and health detection. With the development of deep learning technology, image-based recognition technology has also rapidly extended to various fields, such as agricultural pests, disease identification, tumor marker recognition, wound severity judgment, road wear recognition, and food safety detection...

The present study combined magnetoencephalography (MEG) recordings with fast periodic visual stimulation (FPVS) to investigate automatic neural responses to morphemes in developing and skilled readers. Native English-speaking children ( N  = 17, grade 5-6) and adults ( N  = 28) were presented with rapid streams of base stimuli (6 Hz) interleaved periodically with oddballs (i.e., every fifth item, oddball stimulation frequency: 1.2 Hz). In a manipulation-check condition, tapping into word recognition, oddballs featured familiar words (e...

Reading fluency is based on the automatic visual recognition of words. As a manifestation of the automatic processing of words, an automatic deviance detection of visual word stimuli can be observed in the early stages of visual recognition. To clarify whether this phenomenon occurs with Japanese kanji compounds-since their lexicality is related to semantic association-we investigated the brain response by utilizing three types of deviants: differences in font type, lexically correct or incorrect Japanese kanji compound words and pseudo-kanji characters modified from correct and incorrect compounds...

Handwritten prescriptions and radiological reports: doctors use handwritten prescriptions and radiological reports to give drugs to patients who have illnesses, injuries, or other problems. Clinical text data, like physician prescription visuals and radiology reports, should be labelled with specific information such as disease type, features, and anatomical location for more effective use. The semantic annotation of vast collections of biological and biomedical texts, like scientific papers, medical reports, and general practitioner observations, has lately been examined by doctors and scientists...

Brain visual dynamics encode rich functional and biological patterns of the neural system, and if decoded, are of great promise for many applications such as intention understanding, cognitive load quantization and neural disorder measurement. We here focus on the understanding of the brain visual dynamics for the Amyotrophic lateral sclerosis (ALS) population, and propose a novel system that allows these so- called 'lock-in' patients to 'speak' with their brain visual movements. More specifically, we propose an intelligent system to decode the eye bio-potential signal, Electrooculogram (EOG), thereby understanding the patients' intention...

Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in real-world scenarios, most VSR studies have focused solely on frontal face pictures. To address this issue, we propose an end-to-end sentence-level multi-view VSR architecture for faces captured from four different perspectives (frontal, 30°, 45°, and 60°). The encoder uses multiple convolutional neural networks with a spatial attention module to detect minor changes in the mouth patterns of similarly pronounced words, and the decoder uses cascaded local self-attention connectionist temporal classification to collect the details of local contextual information in the immediate vicinity, which results in a substantial performance boost and speedy convergence...

Deep learning technology has encouraged research on noise-robust automatic speech recognition (ASR). The combination of cloud computing technologies and artificial intelligence has significantly improved the performance of open cloud-based speech recognition application programming interfaces (OCSR APIs). Noise-robust ASRs for application in different environments are being developed. This study proposes noise-robust OCSR APIs based on an end-to-end lip-reading architecture for practical applications in various environments...

Previous behavioural data indicate lower word-nonword recognition accuracy in association with a high level of positive schizotypy, psychopathy, or motor impulsivity traits, each with some unique contribution, in the general population. This study aimed to examine the neural underpinnings of these associations using functional magnetic resonance imaging (fMRI) in a volunteer sample. Twenty-two healthy English-speaking adults completed self-report measures of schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences [O-LIFE]), psychopathy (Triarchic Psychopathy Measure [TriPM]), and impulsivity (Barratt Impulsiveness Scale [BIS-11]) and underwent whole-brain fMRI while performing a lexical decision task (LDT) featuring high and low-frequency words, real nonwords, and pseudohomophones...

Automatic speech recognition (ASR) is the major human-machine interface in many intelligent systems, such as intelligent homes, autonomous driving, and servant robots. However, its performance usually significantly deteriorates in the presence of external noise, leading to limitations of its application scenes. The audio-visual speech recognition (AVSR) takes visual information as a complementary modality to enhance the performance of audio speech recognition effectively, particularly in noisy conditions. Recently, the transformer-based architectures have been used to model the audio and video sequences for the AVSR, which achieves a superior performance...

Image captioning aims at automatically describing images by sentences. It often requires lots of paired image-sentence data for training. However, trained captioning models can hardly be applied to new domains in which some novel words exist. In this paper, we introduce the zero-shot novel object captioning task, where the machine generates descriptions about novel objects without extra training sentences. To tackle the challenging task, we mimic the way that babies talk about something unknown, using the word of a similar known object...