Background: Traditional audiological assessment often does not properly reflect the challenges experienced by cochlear implant (CI) users in complex listening environments. Deficits in speech recognition and sound localization ability persist despite...
Background: the word recognition score (WRS) achieved with cochlear implants (CIs) varies widely. To account for this, a predictive model was developed based on patients’ age and their pre-operative WRS. This retrospective study aimed to find o...
Introduction: This study aimed to compare different scoring methods, such as phoneme, syllable, and word-based scoring, during word recognition in noise testing and their interaction with hearing loss severity. These scoring methods provided a struct...
(1) Background: The study aimed to construct a clinically valuable closet-set WRS test with a picture identification task for young Greek-speaking children. (2) Methods: The test material was meticulously designed based on specific criteria. To deter...
The purpose of the study was to examine the subjective and objective potential advantage for speech understanding in noise achieved by cochlear implant (CI) recipients when using the autosensitivity control (ASC) input signal processing in combinatio...
Background/Objectives: The present study investigates the reasons for better recognition of disyllabic words in Malayalam among individuals with hearing loss. This research was conducted in three experiments. Experiment 1 measured the psychometric pr...
22 July 2021
Written vocabulary size plays a key role in children’s reading development. We aim to study the relationship between Chinese written vocabulary size and cognitive, emotional, and behavioral factors in primary school students. Using stratified cluster...
Background and Objectives: Speech audiometry employs standardized materials, typically in the language spoken by the target population. Language-specific nuances, including phonological features, influence speech perception and recognition. The mater...
21 June 2021
This study focused on the associative learning of new word forms in the first language and haptic stimuli. In this study, healthy Japanese participants performed three-step tasks. First, participants made nine subjective evaluations of haptic stimuli...
In this work, we aim to re-rank the n-best hypotheses of an automatic speech recognition system by punishing the sentences which have words that are semantically different from the context and rewarding the sentences where all words are in semantical...
This study investigates the effects of bilingual proficiency on word recognition and recall across different memory tasks, with a focus on Chinese–English bilinguals. Participants learned lists of words in either their L1 (Chinese) or L2 (Engli...
This study aimed to investigate differences between ears in performance on a monaural word recognition in noise test among individuals across a broad range of ages assessed for (C)APD. Word recognition scores in quiet and in speech noise were collect...
Personality recognition is a classic and important problem in social engineering. Due to the small number and particularity of personality recognition databases, only limited research has explored convolutional neural networks for this task. In this...
Background/Objectives. Vocabulary acquisition is a lifelong process, with the most rapid growth occurring from early childhood to school age. Different contextual factors influence how new vocabulary is acquired across various age groups during readi...
With the development of intelligentization in maritime vessels, the pursuit of an organized and scalable knowledge storage approach for marine engine room systems has become one of the current research hotspots. This study addressed the foundational...
Historical documents refer to records or books that provide textual information about the thoughts and consciousness of past civilisations, and therefore, they have historical significance. These documents are used as key sources for historical studi...
Variation in the language experience of bilinguals has consequences for cognitive and affective processes. In the current study, we examined how bilingual experience influences the relationship between language and emotion in English among a group of...
Background: Neurodivergent students, including those with Autism Spectrum Disorder (ASD) and Attention Deficit/Hyperactivity Disorder (ADHD), frequently encounter challenges in several areas of foreign language (FL) learning, including vocabulary acq...
This study aims to solve the problem of named entity recognition of complex mechanical equipment faults, especially the problems of many professional terms, long sentences, fuzzy entity boundaries, entity nesting, and abbreviation ambiguity, in mine...
Background: The cochlear implant (CI) is an established treatment option for patients with inadequate speech understanding and insufficient aided scores. Nevertheless, reliable predictive models and specific therapy goals regarding achievable speech...
Recurrent neural network (RNN) has achieved remarkable success in sequence labeling tasks with memory requirement. RNN can remember previous information of a sequence and can thus be used to solve natural language processing (NLP) tasks. Named entity...
At present, span-based entity recognition methods are mainly used to accurately identify the span (entity) boundary for entity recognition, in which the relative position information of the span boundary and the information of words in the span regio...
In the medical field, extracting medical entities from text by Named Entity Recognition (NER) has become one of the research hotspots. This thesis takes the chapter-level diabetes literature as the research object and uses a deep learning method to e...
2 September 2021
Previous findings have shown essential connections between linguistic and gustatory stimuli for people with autism or lexical gustatory synesthesia. We examined the associative learning of novel linguistic forms in Japanese as a native language and t...
Speech audiometry tests are a crucial tool in clinical care and research. In Dutch, the common practice is to use lists of monosyllabic words with a consonant-vowel-consonant (CVC) structure. However, there are relatively few lists, and they are shor...
In recent years, online course learning has gradually become the mainstream of learning. As the key data reflecting the quality of online courses, users’ comments are very important for improving the quality of online courses. The sentiment inf...
In the real world, multimodal sentiment analysis (MSA) enables the capture and analysis of sentiments by fusing multimodal information, thereby enhancing the understanding of real-world environments. The key challenges lie in handling the noise in th...
Due to the complexity and technicality of named entity recognition (NER) in the power grid field, existing methods are ineffective at identifying specialized terms in power grid operation record texts. Therefore, this paper proposes a Chinese power v...
With the rapid development of speech assistants, adapting server-intended automatic speech recognition (ASR) solutions to a direct device has become crucial. For on-device speech recognition tasks, researchers and industry prefer end-to-end ASR syste...
Script identification is an essential step in document image processing especially when the environment is multi-script/multilingual. Till date researchers have developed several methods for the said problem. For this kind of complex pattern recognit...
Background: The Chear open-set performance test (COPT), which uses a carrier phrase followed by a monosyllabic test word, is intended for clinical assessment of speech recognition, evaluation of hearing-device performance, and the fine-tuning of hear...
Computer vision offers a promising approach to automating the observation of animal behavior, thereby contributing to improved animal welfare and precision livestock management. However, the absence of standardized behavioral definitions limits the a...
Background: the Bonebridge hearing implant is an active transcutaneous bone conduction implant suitable for various types of hearing loss. It was first launched in 2012 as the BCI 601, with a newer internal part (BCI 602) released in 2019. With the n...
In this work we present a bimodal multitask network for audiovisual biometric recognition. The proposed network performs the fusion of features extracted from face and speech data through a weighted sum to jointly optimize the contribution of each mo...
The Montreal cognitive assessment (MoCA), a widely accepted screening tool for identifying patients with mild cognitive impairment (MCI), includes a language fluency test of verbal functioning; its scores are based on the number of unique correct wor...
Semantic features are very important for machine learning-based drug name recognition (DNR) systems. The semantic features used in most DNR systems are based on drug dictionaries manually constructed by experts. Building large-scale drug dictionaries...
2 March 2020
The resident admit notes (RANs) in electronic medical records (EMRs) is first-hand information to study the patient’s condition. Medical entity extraction of RANs is an important task to get disease information for medical decision-making. For...
The increasing prevalence of Alzheimer’s disease (AD) has become a global phenomenon presenting serious social and health challenges. For detecting early molecular changes in the disease, several techniques to measure varied species of amyloid...
We assessed whether constructing a mathematical knowledge graph for a knowledge question-answering system or a course recommendation system, Named Entity Recognition (NER), is indispensable. The accuracy of its recognition directly affects the actual...
This study deals with an acoustic perceptual test performed on the basis of adaptive matrix tests, which represent a modern and reliable tool that can be used not only in perceptual phonetics but also for detecting problems related to hearing. The te...
Recently, researchers have extensively explored various methods for electronic medical record named entity recognition, including character-based, word-based, and hybrid methods. Nonetheless, these methods frequently disregard the semantic context of...
With the ongoing progress of geological survey work and the continuous accumulation of geological data, extracting accurate information from massive geological data has become increasingly difficult. To fully mine and utilize geological data, this st...
Neural machine translation (NMT) methods based on various artificial neural network models have shown remarkable performance in diverse tasks and have become mainstream for machine translation currently. Despite the recent successes of NMT applicatio...
Named-entity recognition (NER) is a preliminary step for several text extraction tasks. In this work, we try to recognize Kazakh named entities by introducing a hybrid neural network model that leverages word semantics with multidimensional features...
In this article, we present a model for analyzing the co-occurrence count data derived from practical fields such as user–item or item–item data from online shopping platforms and co-occurring word–word pairs in sequences of texts....
(1) Background: Information overload challenges decision-making in the Industry 4.0 era. While Natural Language Processing (NLP), especially Automatic Text Summarization (ATS), offers solutions, issues with factual accuracy persist. This research bri...
Location services based on address matching play an important role in people’s daily lives. However, with the rapid development of cities, new addresses are constantly emerging. Due to the untimely updating of word segmentation dictionaries and...
The goal of Clinical Named Entity Recognition (CNER) is to identify clinical terms from medical records, which is of great importance for subsequent clinical research. Most of the current Chinese CNER models use a single set of features that do not c...
Named Entity Recognition (NER) on Clinical Electronic Medical Records (CEMR) is a fundamental step in extracting disease knowledge by identifying specific entity terms such as diseases, symptoms, etc. However, the state-of-the-art NER methods based o...
Automatic detection and recognition of wheel hub text, which can boost the efficiency and accuracy of product information recording, are undermined by the obscurity and orientation variability of text on wheel hubs. To address these issues, this pape...
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