Speech Therapy Applications Research Articles

A systematic review of the application of machine learning techniques to ultrasound tongue imaging analysis.

B-mode ultrasound has emerged as a prevalent tool for observing tongue motion in speech production, gaining traction in speech therapy applications. However, the effective analysis of ultrasound tongue image frame sequences (UTIFs) encounters many challenges, such as the presence of high levels of speckle noise and obscured views. Recently, the application of machine learning, especially deep learning techniques, to UTIF interpretation has shown promise in overcoming these hurdles. This paper presents a thorough examination of the existing literature, focusing on UTIF analysis. The scope of our work encompasses four key areas: a foundational introduction to deep learning principles, an exploration of motion tracking methodologies, a discussion of feature extraction techniques, and an examination of cross-modality mapping. The paper concludes with a detailed discussion of insights gleaned from the comprehensive literature review, outlining potential trends and challenges that lie ahead in the field.

Utilization of Augmented Reality Technology in Independent Speech Therapy Applications

One of the uses of information technology is augmented reality technology in the health sector. Augmented reality is used in the development of applications that are used for speech therapy for children with autism or children with speech delays. The method used for the development of speech therapy applications is the extreme programming method. This method can adapt to the development of an application in a short time and quite a lot of changes. The stages in the extreme programming method include identifying system requirements, planning activities during system/application development, system development process, iteration for system improvement until the final iteration, and no more user feedback, system/application production, and system maintenance with data backup and system recovery. After testing the system, it was concluded that three iterations occurred during the development of the speech therapy application. The last test showed that the user accepted the speech therapy application with a percentage of 77,14%. The output of this research is an augmented reality-based speech therapy application that is useful for independent speech therapy for children with speech delays.

Efficacy and feasibility of a digital speech therapy for post-stroke dysarthria: protocol for a randomized controlled trial.

Dysarthria is a motor speech disorder caused by various neurological diseases, particularly stroke. Individuals with post-stroke dysarthria experience impaired speech intelligibility, communication difficulties, and a reduced quality of life. However, studies on the treatment of post-stroke dysarthria are lacking. Digital speech therapy applications have the advantages of being personalized and easily accessible. However, evidence for their efficacy is not rigorous. Moreover, no studies have investigated both the acute to subacute, and chronic phases of stroke. This study aims to investigate the efficacy and feasibility of digital speech therapy applications in addressing these gaps in dysarthria treatment. This study is a multicenter, prospective, randomized, evaluator-blinded non-inferiority trial. We aim to recruit 76 participants with post-stroke dysarthria. Eligible participants will be stratified based on the onset period of stroke into acute to subacute, and chronic phases. Participants will be randomized in a 1:1 to receive either a personalized digital speech therapy application or conventional therapy with a workbook for 60 min daily, 5 days a week, for 4 weeks. The primary outcome is the improvement in speech intelligibility. This will be measured by how accurately independent listeners can transcribe passages read by the participants. Secondary outcomes, which include speech function, will be evaluated remotely by speech-language pathologists. This includes the maximum phonation time, oral diadochokinetic rate, and percentage of consonants correct. Participants' psychological well-being will also be assessed using self-report questionnaires, such as depressive symptoms (Patient Health Questionnaire-9) and quality of life (Quality of Life in the Dysarthric Speaker scale). The trial will also assess the feasibility, participant adherence, and usability of the application. Rigorous data collection and monitoring will be implemented to ensure patient safety. This trial aims to investigate the efficacy and feasibility of digital speech therapy applications for treating post-stroke dysarthria. The results could establish foundational evidence for future clinical trials with larger sample sizes. Clinicaltrials.gov, identifier: NCT05865106.

Speech development delay in autism spectrum disorder – the perspective of using the “Talk To Me” speech therapy application

Introduction and aim. The paper aims to present the prospects of using the „Talk To Me” application in the case of a child with this neurodevelopmental disorder. Description of the case. The subject of the study was a 53-month-old boy who did not communicate verbally, but behaved forcefully. A child underwent a speech therapy using the „Talk To Me” application for a period of 12 weeks. The scale of acquiring language skills in the field of communication competence was used to monitor the progress of therapy. In the analyzed period, a decrease in the score on the scale from 23 to 15 points was observed, which means a result indicating an improvement in the communication sphere. The use of a newly developed therapeutic tool was an important motivational factor and, in the opinion of the boy’s mother, significantly influenced the progress in therapy, which had not been observed before using a conventional approach. Conclusion. The „Talk To Me” application is a therapeutic tool with potential effectiveness in the case of speech delays in children with autism spectrum disorder, and it is also compatible with behavioral therapy, a widely used therapeutic method with proven effectiveness in autism spectrum disorder.

Utilization of AR Technology for The Development of Speech Therapy Applications by Optimizing Marked-Based Tracking Method

Autism is a developmental disorder that attacks children mentally and causes difficulties in interacting with the social environment. Therapy that can be done to people with autism to deal with communication disorders is speech therapy. Application usage health or better known as mobile health is easy and fast to help users in accessing information about various health problems, one of which is child development or better known as an autism spectrum disorder (ASD) which was developed using augmented reality (AR) technology. The purpose of the study is to optimizing the marked-based tracking method to augmented reality technology for speech therapy tutorials for children with autism. The results obtained from this study are the SELPY application (Self Autism Therapy) mobile-based speech therapy for people with autism which is a product of the application of appropriate technology in the field of information technology, especially in the health sector. The marked-based tracking method has been successfully implemented in the development of speech therapy AR applications for children with autism spectrum disorder (ASD). This is by the results of the tests that have been carried out, namely distance testing and angle testing. The most ideal distance to detect marker/image targets is 40cm to 50cm with a smartphone tilt angle of 200 to 300.

Development of Application for Early Intervention Speech Therapy in Children with Intellectual Disability

This study aims to describe the stages of the speech therapy application development process. This research produces an android application product that can be used in early intervention in speech therapy for children with intellectual disabilities. This development research is based on the development method of Gall, et al. (2007), and only carried out up to five stages, namely: 1) Research and information collecting (searching and collecting data), 2) Planning, 3) Develop preliminary form of product, 4) Preliminary field testing, 5) Main product revision. The data collection method in the form of a Likert scale was used in this study. Media validation was carried out by speech therapy content experts and media experts. The validation results from content experts obtained a score with a percentage of 88 percent and validation from media experts obtained a score of 93 percent. This indicates a very valid category, and this application is declared feasible and can be used. The results of the implementation for children with intellectual disabilities by giving a questionnaire obtained a percentage of 85 percent. So it can be concluded that the speech therapy application media is well used.Development of Application for Early Intervention Speech Therapy in Children with Intellectual Disability

An Intelligent reference free adaptive learning algorithm for speech enhancement

Removing of noise component is an important task in all practical applications like hearing aids, speech therapy etc. In speech communication applications the speech components are contaminated with various types of noises. Separation of speech and noise component is a key issue in hearing aids, speech therapy applications. This paper demonstrates a hybrid version of singular spectrum analysis (SSA) and independent component analysis (ICA) based adaptive noise canceller (ANC) to separate noise and speech components. As ICA is not suitable for single channel sources, SSA is used to map signal channel data to multivariant data. Therefore, SSA based ICA decomposition is used to generate reference for noise cancellation process. Variable Step based adaptive learning algorithm is used to separate noise contaminations from speech signals. To reduce computational complexity of system, sign regressor operation is applied to the data vector of the proposed adaptive learning methodology. Performance measures such as Signal to noise ratio improvement, excess mean square error and misadjustment are calculated for various considered ANCs, their values for crane noise are 29.6633 dB, – 27.4854 dB and 0.2058 respectively. Among the various adaptive learning algorithms, sign regressor based step variable method performs better than the other algorithms. Hence this learning methodology is well suited for hearing aids and speech therapy applications due to its robustness, less computational complexity and filtering ability.

A Speech Therapy Application for Improvising Soft Skills of Born Deaf

Regular active listening is necessary for the deaf and hard hearing people (DHH) in their hearing recovery, but the associated hearing activities are typically not adequate for them for reasons of some sort. Although some new desktop computer-assisted tools have been developed to facilitate active listening, the rate of usage is not high. Game applications are better tools for activity base training. Especially, for the DHH, however, limited software is available on the market, particularly to involve them in active listening and speaking. Therefore, this platform base software is the impetus for growing their active listening daily. The feature motivates and excites them as part of the workout, using their voice to play games. A vocal training program relies on the feedback of the special help provided by the schools and the challenges they encounter when teaching how to develop their skills manually.

Feasibility of Automatic Speech Recognition for Providing Feedback During Tablet-Based Treatment for Apraxia of Speech Plus Aphasia.

Purpose Individuals with neurogenic speech disorders require ongoing therapeutic support to achieve functional communication goals. Alternative methods for service delivery, such as tablet-based speech therapy applications, may help bridge the gap and bring therapeutic interventions to the patient in an engaging way. The purpose of this study was to evaluate an iPad-based speech therapy app that uses automatic speech recognition (ASR) software to provide feedback on speech accuracy to determine the ASR's accuracy against human judgment and whether participants' speech improved with this ASR-based feedback. Method Five participants with apraxia of speech plus aphasia secondary to stroke completed an intensive 4-week at-home therapy program using a novel word training app with built-in ASR. Multiple baselines across participants and behaviors designs were employed, with weekly probes and follow-up at 1 month posttreatment. Four sessions a week of 100 practice trials each were prescribed, with 1 being clinician-run and the remainder done independently. Dependent variables of interest were ASR-human agreement on accuracy during practice trials and human-judged word production accuracy over time in probes. Also, user experience surveys were completed immediately posttreatment. Results ASR-human agreement on accuracy averaged ~80%, which is a common threshold applied for interrater agreement. All participants demonstrated improved word production accuracy over time with the ASR-based feedback and maintenance of gains after 1 month. All participants reported enjoying using the app with support of a speech pathologist. Conclusion For these participants with apraxia of speech plus aphasia due to stroke, satisfactory gains were made in word production accuracy with an app-based therapy program providing ASR-based feedback on accuracy. Findings support further testing of this ASR-based approach as a supplement to clinician-run sessions to assist clients with similar profiles in achieving higher amount and intensity of practice as well as empowering them to manage their own therapy program. Supplemental Material https://doi.org/10.23641/asha.8206628.

Implicit theory manipulations affecting efficacy of a smartphone application aiding speech therapy for Parkinson's patients.

A Smartphone speech-therapy application (STA) is being developed, intended for people with Parkinson's disease (PD) with reduced implicit volume cues. The STA offers visual volume feedback, addressing diminished auditory cues. Users are typically older adults, less familiar with new technology. Domain-specific implicit theories (ITs) have been shown to result in mastery or helpless behaviors. Studies manipulating participants' implicit theories of 'technology' (Study One), and 'ability to affect one's voice' (Study Two), were coordinated with iterative STA test-stages, using patients with PD with prior speech-therapist referrals. Across studies, findings suggest it is possible to manipulate patients' ITs related to engaging with a Smartphone STA. This potentially impacts initial application approach and overall effort using a technology-based therapy.

An Evaluation of the Aurora System as a Flesh-Point Tracking Tool for Speech Production Research

Northern Digital Instruments (NDI; Waterloo, Ontario, Canada) manufactures a commercially available magnetometer device called Aurora that features real-time display of sensor position tracked in 3 dimensions. To test its potential for speech production research, data were collected to assess the measurement accuracy and reliability of the system. First, sensors affixed at a known distance on a rigid ruler were moved systematically through the measurement space. Second, sensors attached to the speech articulators of a human participant were tracked during various speech tasks. In the ruler task, results showed mean distance errors of less than 1 mm, with some sensitivity to location within the measurement field. In the speech tasks, Euclidean distance between jaw-mounted sensors showed comparable accuracy; however, a high incidence of missing samples was observed, positively correlated with sensor velocity. The real-time positional feedback provided by the system makes it potentially useful in speech therapy applications. The overall missing data rate observed during speech tasks makes use of the system in its current form problematic for the quantitative measurement of speech articulator movements; however, NDI is actively working to improve the Aurora system for use in this context.

A novel instrument to measure acoustic resonances of the vocal tract during phonation

Acoustic resonances of the vocal tract give rise to formants (broad bands of acoustic power) in the speech signal when the vocal tract is excited by a periodic signal from the vocal folds. This paper reports a novel instrument which uses a real-time, non-invasive technique to measure these resonances accurately during phonation. A broadband acoustic current source is located just outside the mouth of the subject and the resulting acoustic pressure is measured near the lips. The contribution of the speech signal to the pressure spectrum is then digitally suppressed and the resonances are calculated from the input impedance of the vocal tract as a function of the frequency. The external excitation signal has a much smaller harmonic spacing than does the periodic signal from the vocal folds and consequently the resonances are determined much more accurately due to the closer sampling. This is particularly important for higher pitched voices and we demonstrate that this technique can be markedly superior to the curve-fitting technique of linear prediction. The superior frequency resolution of this instrument which results from external vocal tract excitation can provide the precise, stable, effective, articulatory feedback considered essential for some language-learning and speech-therapy applications.

Amplifier filter system for speech therapy

Am amplifier filter system for speech therapy applications. This apparatus combines a direct channel amplifier and two band pass filter amplifiers such that selected phonemes (speech sounds) of the spoken word can be enhanced so that a speaker can be taught corrections for various articulation deficiencies. Through the choice of optimum center frequencies in one-octave bandpass filters for various phonemes of a given language, a selected portion of the acoustic spectrum within the language can be enhanced to achieve this result. The apparatus is highly portable, light weight and is affordable. It provides for inputs from microphones and/or tape recorders, and outputs to earphones, loudspeakers, vibrators, and/or tape recorders. Because of the unique design of this unit, it is "user friendly" thus making it useful in both the presence of a clinician and by a client during his or her own therapy. A particular response at each of the center frequencies is selected to have a 12-14 dB slope which has been found to provide the optimum enhancements of the acoustic spectra of the various phonemes.