Hearing Persons Research Articles

Revitalize Hearing Skills with Advanced Speech Processing Technology

Revitalizing listening skills with advanced sound processing technology is an interesting concept, especially in today's digital era where technology is advancing rapidly. Listening skill is the ability to understand, analyze, and respond well to information conveyed through sound, and this is a key skill in various contexts, such as interpersonal communication, business, education, and others. Here are some ways revitalizing hearing skills with advanced sound processing technologies can be accomplished, Introduction to Sound Processing Technologies, It is important to understand what advanced sound processing technologies are. This includes using speech processing algorithms, speech recognition techniques, and even artificial intelligence (AI) to optimize speech understanding and interpretation. Hearing Skills Training Speech processing technology can be used in hearing skills training. For example, an application that can record, analyze and provide feedback on a person's hearing ability. Such applications can be used in the context of business education or training. Automatic Transcription and Translation, Voice processing technology can be used to convert conversations in foreign languages ??into text or translate voice content in real time. This can help someone understand a foreign language or content displayed in a language they are not familiar with. Improved Business Communications, In business, voice processing technology can be used to record, analyze and provide feedback on presentations, meetings or telephone conversations. This can help improve business communication skills. Providing Better Customer Service Many companies use voice processing technology to improve their customer service. Advanced voice interactive systems (IVR) can be used to route customer calls more efficiently and provide necessary information. Sentiment Understanding Advanced voice processing technology can be used to analyze sentiment in conversations or customer reviews. This can help companies understand the views and feelings of their customers. Educational Applications Speech processing technology can also be used in education to create more interactive teaching materials.

Prevalence and Factors Associated With Occupational Noise-Induced Hearing Loss Among Palm Oil Mill Workers in Selangor, Malaysia.

Introduction Occupational noise-induced hearing loss (NIHL) continues to be a significant public health issue globally, with Malaysia being no exception. In Malaysia, the majority of NIHL cases are reported from the manufacturing sector, with Selangor among the states with the highest number of confirmed cases. This study aimed to assess the prevalence of and factors associated with occupational NIHL among palm oil mill workers in Selangor, Malaysia. Methods A cross-sectional study was conducted to analyze the data from the data collection form, noise risk assessment reports, and audiometric test results done between 2021 and 2022 with a comparable baseline audiometric test. Results A total of 143 participants from three palm oil mills joined this study. The prevalence of NIHL was 42.7% (n = 61). Following the logistic regression model, NIHL was significantly associated with a duration of employment of 10 years and above, a history of occupational noise exposure at the previous workplace, and the use of personal hearing protectors at the current workplace with an adjusted OR of 2.41 (95% CI (1.14, 5.07)), 5.89 (95% CI (2.38, 14.53)), and 0.36 (95% CI (0.16, 0.83)), respectively. Conclusion The prevalence of NIHL among the study participants was high, and the associated factors are modifiable factors that can be prevented with a comprehensive hearing conservation program in the palm oil mills.

Enhancing Sign Language Understanding through Machine Learning at the Sentence Level

Abstract: The visual language of sign language is based on nonverbal communication, including hand and body gestures. When it comes to communicating, it is the main tool for those who are deaf or hard of hearing all around the globe. Useful for both hearing and deaf persons, this can translate sign language into sentences in real-time or help those who are hard of hearing communicate with others. This work focuses on developing a sentence-level sign language detection system utilizing a custom dataset and Random Forest model. Leveraging tools such as Media Pipe and TensorFlow, we facilitate gesture detection. Through continuous detection of gestures, we generate a list of corresponding labels. These labels are then used to construct sentences automatically. The system seamlessly integrates with ChatGPT, allowing direct access to generate sentences based on the detected gestures. Our custom dataset ensures that the model can accurately interpret a wide range of sign language gestures. Our method helps close the communication gap between people who use sign language and others, with an accuracy of 80%, by merging machine learning with complex language models.

From alert to action: earthquake early warning and deaf communities

AbstractEarthquake early warning (EEW) alerts may give people valuable seconds to take protective action, such as drop, cover and hold on, before earthquake shaking starts. In order for individuals to take protective action, they need to receive the alert, understand the alert message, and have enough contextual knowledge to take appropriate protective action. Deaf and hard of hearing (DHH+) persons do not have equitable access to earthquake information, warning systems, training, and participation in disaster decision-making at all levels. Despite international policies for emergency alerts to be accessible to people with disabilities, there are no research publications that specifically address the effectiveness of EEW alerts for DHH+ communities. Missed notifications and misunderstandings about elements of the EEW alert message can delay the response time of DHH+ persons. Furthermore, unequal access to earthquake drills and preparedness information can leave DHH+ persons with insufficient context to take protective action when receiving alerts. The existing gaps in effectiveness of the EEW alerts stem from language inequities for DHH+ persons in our schools, workplaces and families, which we analyze by applying linguistic anthropological and sociolinguistic frameworks to examine the nexus of DHH+ communities’ languages and EEW messaging. To advance language equity in EEW alerting, inclusion of DHH+ communities can improve messaging and reduce misunderstandings so that DHH+ persons can quickly take protective action when they receive an alert.

Overview of the Prevalence and Contributing Factors for Occupational Noise-Induced Hearing Loss (NIHL) in Malaysia

INTRODUCTION: This manuscript aims to provide a synopsis of the current situation surrounding noise exposure at work and the risk of noise-induced hearing loss (NIHL) in Malaysia. NIHL is an occupational illness that affects most many people and can be prevented in many countries in the world. The production and agriculture businesses and the extraction of natural resources and urban traffic all contribute to ambient noise levels. Working in a noisy environment is the main occupational risk factor for adult-onset hearing loss. In this study, we investigate the prevalence of NIHL across different industries, as well as research publication trends on NIHL. MATERIAL AND METHODS: Conducted thorough several online databases, like Science Direct, Web of Science, and Google Scholar, for related research that had already been published. The review phases were carried out according to the recommendations laid out by the preferred reporting items for systematic reviews. A set of criteria was developed for selecting relevant studies. RESULTS: The prevalence of NIHL among workers in Malaysia, varies across different industries and has been reported to range from 5.0% to 82.6%. NIHL has multiple contributing factors, including noise intensity, long-term exposure to daily noise, hearing protection devices and age. A review of these studies found varying percentages of individuals affected by each contributing factor. CONCLUSION: Occupational NIHL is a preventable health risk for workers across industries. Employers must adopt engineering and administrative controls (education and training) and provide personal hearing protectors to protect workers from noise.

Bidirectional Braille-speech Communication System for Deafblind Students

Deafblindness is a type of dual disability wherein both visual and auditory capabilities are significantly impaired. Special communication methods have been developed for the deafblind community, yet these methods require that both people involved have prior knowledge and training to successfully communicate; limiting deafblind people’s social interactions, particularly in academic settings. This paper describes the development of a device that enables two-way communication between a severe to profoundly deafblind user and a hearing person with no prior knowledge of Braille and no additional intermediaries. A Convolutional Neural Network (CNN) scheme for speech recognition was designed and implemented along with the development of an algorithm capable of developing both text-to-speech and Finger-Braille-to-text conversion. Lastly, a system integration via 3D modelling and additive manufacturing was carried out to deliver a functional prototype. The resulting device aims to allow deafblind students to send and receive information entirely in finger Braille, using buttons and vibrotactile feedback, while the hearing tutor receives auditory messages and speaks to reply, making the educational experience as familiar as possible for both parties. Users testing the device achieved an average typing accuracy of over 95% and demonstrated understanding of commands transmitted through the device’s components.

Defining hearing culture in context of Deaf culture: A grounded theory examination

This research aims to define and identify the characteristics of hearing culture in the United States, particularly in contrast to Deaf culture. Through three focus group interviews with 18 participants from different backgrounds, including deaf individuals with both deaf and hearing parents, as well as hearing individuals affiliated with the Deaf community, key themes emerged. These themes included defining cultures, audiovocal orientation, mixed spaces, negotiating one’s role as a hearing person, perception, development of hearing identity, and orientation. This study seeks to shed light on the ways in which hearing individuals navigate the world with their primary senses of listening and speaking, in contrast to deaf individuals who rely on vision and touch. Ultimately, this research aims to provide a better understanding of the complexities of cultural dynamics between the hearing and Deaf worlds. Ultimately, a definition of hearing culture emerged from the data.

Gesture generation by the robotic hand for aiding speech and hard of hearing persons based on indian sign language

Speech and hearing impairments are among the most common problems in Indian societies. It can affect anyone, whether children, adults, or more. Many different treatments can help to overcome hearing problems. Different types of hearing aids and cochlear implants help amplify sounds for better hearing. The type of language known as sign language is very scientific and has its grammar and syntax. Still, due to a need for more awareness among hard-of-hearing persons, they need to be made familiar with the institutions where they can learn and equip themselves for communication. This paper describes an approach to aid speech and hard-of-hearing persons so that they are free to communicate with persons who do not have speech and hearing disabilities based on the Indian Sign Language System. To find an appropriate solution, there is a need to develop a system that can act as an interpreter for speech and hard-of-hearing persons. The interpreter system is designed with the help of the Robotic hand model and is programmed using Raspberry Pi 4. Based on the experimental results, it can be observed that the robotic hands generated different signs of the alphabet corresponding to the speech commands uttered by an individual. Several experimental trials were conducted by ten persons who do not have any hearing disabilities. The results of the five experimental trials are shown in this paper. The estimation of performance parameters and statistical analysis are also carried out to analyze better and interpret the experimental results. Based on the experimental results, the proposed robotic hand interpreter system model accurately generates gestures corresponding to different alphabets used in the Indian Sign Language system, yielding an overall accuracy of 94 percent.

Two-Way Sign Language Translator for Visually Impaired People

Hearing disabilities affect people all over the world. Nearly 360 million people have a disabling hearing loss. In the recent years, there has been a rapid increase in the number of deaf and dumb victims due to birth defects, accidents and oral diseases. Since deaf and dumb people cannot communicate with a hearing person, they have to depend on some sort of visual communication. Sign Language is not understood by the majority of hearing people. The objective of our project is to form a bridge between the hearing-impaired community and the hearing community; to further commence a two-way communication. We propose a two-way sign language translator that converts Voice to sign language and vice versa in real time. We process the video frame by frame using the OpenCV Library in Python. Furthermore, we use background subtraction method called Gaussian Mixture-based Background/Foreground Segmentation Algorithm on each frame to subtract the background. Contours of this processed image are then passed into a Deep Neural Net (DNN) to classify the frame to the corresponding written language equivalent words. For conversion from sign language to voice, we use basic Natural Language Processing and gtts to accurately conserve the grammar in the sign language. The enrolment rate and literacy among the hearing-impaired children is far below the average for the population at large. This technology will then help the normal schools better integrate the hearing-impaired community thus making education more accessible and cheaper for them. Speech Emotion Recognition (SER) is a vital aspect of human-computer interaction and emotional intelligence applications. This SER that employs Mel- frequency cepstral coefficients (MFCC) as the basis for feature extraction, followed by a Convolutional Neural Network (CNN) with a customized architecture for emotion classification. The methodology 2 involves transforming audio samples into MFCC images, enabling the application of CNNs typically used in computer vision tasks. This fusion of traditional audio analysis with deep learning techniques harnesses the power of MFCC's spectral representation and CNN's spatial pattern recognition. By modifying the CNN architecture, the model can better discern emotional cues in the MFCC images, enhancing SER performance. This strategy offers SER a viable path forward, with the ability to identify complex emotional expressions. In order to increase the accuracy of emotion recognition, it tackles the requirement for feature-rich representations and sophisticated modelling techniques. KEYWORDS: OpenCV, DNN, SER, CNN, MFCC

DIFFERENCES BETWEEN THE CREATIVITY OF PEOPLE WHO ARE DEAF OR HARD OF HEARING AND THOSE WITH TYPICAL HEARING: A PROTOCOL FOR THE FURTHER SCOPING REVIEW

As a step prescribed by the Joanna Briggs Institute methodology before conducting a scoping review, the protocol aims to describe differences in creativity between deaf and hard of hearing and typically hearing people. Creativity as a mental process is important for the development of personality, imagination, communication skills, and interpersonal relationships. For this study, the focus was on creativity of deaf and hard of hearing persons. Deaf and hard of hearing people show specific characteristics in their mode of creativity. All the studies that deal with creativity in deaf and hard of hearing people will be included. Studies of any design in English, German, or Czech will be accepted as sources for assessment and analysis for systematic review. The Joanna Briggs Institute methodology for a scoping review will act as a framework for the review that will be prepared. 14 scientific databases will be chosen for this review. Two independent reviewers will identify and evaluate all the titles and abstracts that are acquired. The selected data will be extracted and reported in tabular form and a descriptive format.

Utilizing Artificial Neural Networks for Establishing Hearing-Loss Predicting Models Based on a Longitudinal Dataset and Their Implications for Managing the Hearing Conservation Program

BackgroundThough the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers. MethodsA comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions. ResultsThe dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend. ConclusionsA consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.

535 - Exploring the Intersectionality of Being Deaf and Black while Accessing Dermatological Care

Abstract In 2021, Deaf or hard of hearing (DHH) persons made up ∼3.4% of the United States population however, there was no sub-categorical data about race. This dearth of data makes it challenging to quantify the health disparities amongst Black DHH individuals. This paper aims to identify trends and disparities to improve health outcomes for DHH and Black patients seeking dermatologic care. Black patients utilize less preventative service, have lower post-trauma survival, and a 3-fold higher risk of maternal mortality than White patients. DHH patients experience delayed cancer treatment, more emergency department visits, and higher intimate partner violence than hearing patients. Black DHH patients have a higher likelihood of cancer, diabetes, hypertension, and lung disease than Black-hearing patients. Black patients have lower survival rates with certain cutaneous neoplasms and poorer disease control than White counterparts. The literature lacks dermatologic care outcomes for Black DHH patients. Shared themes impacting Black and DHH patients’ care include audism and racism, medical mistrust, and poor communication with clinicians. Unfortunately, the dermatological experiences of Black DHH patients are poorly documented. To minimize disparities for this population, clinicians must acknowledge them and partner with the community to investigate them.

The clinical use of personal hearing amplifiers in facilitating accessible patient-provider communication: A scoping review.

Older adults with hearing loss struggle to communicate with care providers and experience higher mortality rates when hospitalized (Genther et al., 2015), even after controlling for age and comorbidities. Personal hearing amplifiers (PHAs), (e.g., Pocketalkers™), can improve communication with older patients. We conducted a scoping review to identify research gaps and summarize findings on the clinical use of PHAs with patients with hearing loss. After refining search terms relating to hearing loss and PHAs, we searched MEDLINE, Embase, PsycINFO, Cochrane Library, CINAHL Complete, Web of Science Core Collection, ERIC (Proquest), PubMed, ClinicalTrials.gov, International Clinical Trials Registry Platform, and the International Standard Randomised Controlled Trial Number Registry. We identified articles published in English between 1980 and 2022 that reported empirical outcomes relating to PHA use in clinical settings. Two reviewers independently extracted data from articles. We then organized data into an evidence map, and a narrative review summarizing outcomes. From 4234 initially identified titles and abstracts, 12 met our criteria as full texts. These included three surveys on clinicians' awareness and use of PHAs, one evaluation of the acoustic output of a PHA, and eight interventions wherein PHAs were provided to patients with hearing loss. These papers used 10 different terms for PHAs and largely did not cite one another. Results showed high levels of satisfaction with PHAs, and consistently improved speech understanding. Despite this, care providers used devices inconsistently, with challenges around provider awareness, and device maintenance and location tracking. PHAs have a consistent positive effect on patients' ability to understand their care providers despite hearing loss. Barriers and facilitators to their use in clinical settings should be further explored.

Comparative Effectiveness of Personal Sound Amplification Products Versus Hearing Aids for Unilateral Hearing Loss: A Prospective Randomized Crossover Trial.

This study compared hearing outcomes with use of personal sound amplification products (PSAPs) and hearing aids (HAs) in patients with moderate to moderately severe unilateral hearing loss. Thirty-nine participants were prospectively enrolled, and randomly assigned to use either one HA (basic or premium type) or one PSAP (basic or high-end type) for the first 8 weeks and then the other device for the following 8 weeks. Participants underwent a battery of examinations at three visits, including sound-field audiometry, word recognition score (WRS), speech perception in quiet and in noise, real-ear measurement, and self-report questionnaires. Functional gain was significantly higher with HAs across all frequencies (P < 0.001). While both PSAPs and HAs improved WRS from the unaided condition, HAs were superior to PSAPs. The speech recognition threshold in quiet conditions and signal-to-noise ratio in noisy conditions were significantly lower in the HA-aided condition than in the PSAP-aided condition, and in the PSAP-aided condition than in the unaided condition. Subjective satisfaction also favored HAs than PSAPs in questionnaires, Abbreviated Profile of Hearing Aid Benefit, International Outcome Inventory for Hearing Aids, and Host Institutional Questionnaire. While PSAPs provide some benefit for moderate to moderately severe unilateral hearing loss, HAs are more effective. This underscores the potential role of PSAPs as an accessible, affordable first-line intervention in hearing rehabilitation, particularly for individuals facing challenges in accessing conventional HAs.

The ineffective emotion regulation of deaf college students: an ERP study.

Deaf students have more difficulties with emotion regulation due to their hearing loss. They are suffering higher socio-emotional risk than the hearing person. But there are few studies explored the neural mechanisms of impaired emotion regulation in the deaf college students. Thirty hearing college students and 27 deaf college students completed the emotion regulation task while recording ERP data and subjective emotion intensity. Behavioral results found that deaf college students had higher emotional experience intensity compared to healthy controls. The ERP results showed the deaf college students had lower LPP amplitudes both using reappraisal and suppression strategies. Moreover, the LPP of expression suppression was associated with the increase of depression scores among deaf college students. Deaf college students may have impaired emotion regulation so that they are more accustomed to using expression suppression strategies to regulate their negative emotions which lead to high risk to be depression.

Training simulator for evaluating the effectiveness of personal noise protection equipment

A description of the laboratory simulator created at Murom Institute for the study of personal hearing protection equipmnent against acoustic noise is presented. General issues of assessing the effectiveness of such equipment are considered. It is shown that in the conditions of the educational process it is sufficient to use a laboratory simulator in the form of a human head manikin, equipped with the hearing organs’ simulators and microphones. The simulator includes a manikin head with a built-in microphone and the internal cavity filled with noise-absorbing material. The microphone is installed so that its center line coincides with the center line of the auricle auditory canal and its working surface (membrane location area) completely covers the hole cross-section in the holder, excluding the sound wave penetration into the area behind the microphone.The second microphone is placed in a special holder near the manikin and provides the noise sound pressure level monitoring in the area where the manikin is installed. Processing of the generated signals is carried out using a program for analyzing spaced acoustic noise based on LabView. Several pairs of electret microphone capsules for general use, type wm61, were selected for the simulator. The first measurements, showing the fundamental possibility of using the simulator in the educational process in the “Technosphere Safety” field of study, were carried out. It is shown that in the octave ranges, measurement accuracy can be ensured at a level of +3 ÷ -0.5 dB, which corresponds to the “Type 2” class in the ANSI system adopted in the USA.

Occupational Noise Induced Hearing Loss in Motor Boat Fisherman

Introduction: Noise Induced Hearing Loss is a person's hearing loss either partially or completely which is permanent and can affect one or both ears caused by continuous exposure to noise in the work environment. One of the causes of Noise Induced Hearing Loss (NIHL) is working as a motorboat fisherman.&#x0D; Content: NIHL can arise as a result of the interaction between genetic factors and environmental factors with the role of internal and external risk factors. The diagnosis of NIHL can be established through history taking, physical examination such as otoscopy and tuning fork tests, as well as supporting examinations in the form of pure tone audiometry.&#x0D; Conclusion: NIHL will produce the impression of sensorineural deafness with a permanent nature so that the only treatment that can be given is supportive and preventive management.&#x0D; Keywords: Noisy; noise-induced hearing loss; motorboat fisherman

Computer vision-based six layered ConvNeural network to recognize sign language for both numeral and alphabet signs

People who have trouble communicating verbally are often dependent on sign language, which can be difficult for most people to understand, making interaction with them a difficult endeavor. The Sign Language Recognition (SLR) system takes an input expression from a hearing or speaking-impaired person and outputs it in the form of text or voice to a normal person. The existing study related to the Sign Language Recognition system has some drawbacks, such as a lack of large datasets and datasets with a range of backgrounds, skin tones, and ages. This research efficiently focuses on Sign Language Recognition to overcome previous limitations. Most importantly, we use our proposed Convolutional Neural Network (CNN) model, “ConvNeural”, in order to train our dataset. Additionally, we develop our own datasets, “BdSL_OPSA22_STATIC1” and “BdSL_OPSA22_STATIC2”, both of which have ambiguous backgrounds. “BdSL_OPSA22_STATIC1” and “BdSL_OPSA22_STATIC2” both include images of Bangla characters and numerals, a total of 24,615 and 8437 images, respectively. The “ConvNeural” model outperforms the pre-trained models with accuracy of 98.38% for “BdSL_OPSA22_STATIC1” and 92.78% for “BdSL_OPSA22_STATIC2”. For “BdSL_OPSA22_STATIC1” dataset, we get precision, recall, F1-score, sensitivity and specificity of 96%, 95%, 95%, 99.31% , and 95.78% respectively. Moreover, in case of “BdSL_OPSA22_STATIC2” dataset, we achieve precision, recall, F1-score, sensitivity and specificity of 90%, 88%, 88%, 100%, and 100% respectively.

Earplug fit-testing system applying pure-tone audiometer

As for the sound attenuation measurement method of hearing protectors, such as earplugs and earmuffs, the real-ear attenuation at threshold (REAT) method is established by some standards such as ISO, ANSI, AS, etc. As known, however, sound attenuation differences between workers wearing protectors in real occupational noise fields are not small due to personal size-fitness or wearing conditions of hearing protectors. Although personal hearing protector fit-testing systems have been developed and standardized in Western countries, the systems have not yet been standardized in Japan, so they are not applicable easily. The authors tried to apply the pure-tone audiometric system equipped with circumaural earphones used for a medical check-up to the fitting system for earplugs on this occasion, where the Japanese guidelines for preventing noise-induced impairments were revised for the first time in about 30 years. This paper describes the overview of the earplug fit-test system applying the audiometer and trial test results of sound attenuation ratings by the proposed system.

Neural envelope tracking predicts speech intelligibility and hearing aid benefit in children with hearing loss

Early assessment of hearing aid benefit is crucial, as the extent to which hearing aids provide audible speech information predicts speech and language outcomes. A growing body of research has proposed neural envelope tracking as an objective measure of speech intelligibility, particularly for individuals unable to provide reliable behavioral feedback. However, its potential for evaluating speech intelligibility and hearing aid benefit in children with hearing loss remains unexplored. In this study, we investigated neural envelope tracking in children with permanent hearing loss through two separate experiments. EEG data were recorded while children listened to age-appropriate stories (Experiment 1) or an animated movie (Experiment 2) under aided and unaided conditions (using personal hearing aids) at multiple stimulus intensities. Neural envelope tracking was evaluated using a linear decoder reconstructing the speech envelope from the EEG in the delta band (0.5-4 Hz). Additionally, we calculated temporal response functions (TRFs) to investigate the spatio-temporal dynamics of the response. In both experiments, neural tracking increased with increasing stimulus intensity, but only in the unaided condition. In the aided condition, neural tracking remained stable across a wide range of intensities, as long as speech intelligibility was maintained. Similarly, TRF amplitudes increased with increasing stimulus intensity in the unaided condition, while in the aided condition significant differences were found in TRF latency rather than TRF amplitude. This suggests that decreasing stimulus intensity does not necessarily impact neural tracking. Furthermore, the use of personal hearing aids significantly enhanced neural envelope tracking, particularly in challenging speech conditions that would be inaudible when unaided. Finally, we found a strong correlation between neural envelope tracking and behaviorally measured speech intelligibility for both narrated stories (Experiment 1) and movie stimuli (Experiment 2). Altogether, these findings indicate that neural envelope tracking could be a valuable tool for predicting speech intelligibility benefits derived from personal hearing aids in hearing-impaired children. Incorporating narrated stories or engaging movies expands the accessibility of these methods even in clinical settings, offering new avenues for using objective speech measures to guide pediatric audiology decision-making.