• Phonetics and Speech Sciences
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• v.11 no.1
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• pp.51-61
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• 2019

The purpose of this study was to develop a smartphone based voice therapy program for patients with voice disorders. Contents of voice therapy were collected through analysis of mobile contents related to voice therapy in Korea, experts and users' demand survey, and the program was developed using Android Studio. Content needed for voice therapy was collected through analysis of mobile contents related to voice therapy. The user satisfaction evaluation for application was conducted for five patient with functional voice disorders. The results showed that the mobile contents related to voice therapy in Korea were mostly related to breathing, followed by voice and singing, but only 13 applications were practically practiced for voice therapy. Expert and user demand surveys showed that the patients and therapists both had a high need for content that could provide voice training in places other than the treatment room. Based on this analysis, 'Home Voice Trainer', an smartphone based voice therapy program, was developed. Home Voice Trainer is an application for voice therapy and management based on Android smartphones. It is designed to train voice therapy activities at home that have been trained offline. In addition, the records of voice training of patients were managed online so that patients can maintain voice improvement through continuous voice consulting even after the end of voice therapy. User evaluations show that patients are satisfied with the difficulty and content of voice therapy programs provided by home voice trainers, but lack of a portion of user interface, such as the portion of home button and interface between screens. Further study suggests the clinical application of home voice trainer to the patients with voice disorders. It is expected that the development study and the clinical application of smart contents related to voice therapy will be actively conducted.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.33 no.3
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• pp.183-187
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• 2022

Dysphonia is well known as one of the otolaryngological symptoms of coronavirus disease 2019 (COVID-19) infection. The vocal changes of the COVID-19 condition have been reported in terms of parameters of multi-dimensional voice assessment, including acoustic analysis, auditory-perceptual evaluation, and psychometric assessment. However, there has not been a daily followup study in patients with acute COVID-19 infection. In this study, a 41-year-old male performed daily voice recordings of vowel phonation and passage-reading tasks during the self-quarantine period of one week. Compared to the normal voice status of the prepandemic period, voice abnormalities peaked on day two after the diagnosis of COVID-19 infection and recovered after one week.

• MALSORI
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• no.64
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• pp.77-88
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• 2007

Nowadays, mel-frequency cesptral coefficients (MFCCs) and Gaussian mixture models (GMMs) are used for the pathological voice detection. This paper suggests a method to improve the performance of the pathological/normal voice classification based on the MFCC-based GMM. We analyze the characteristics of the mel frequency-based filterbank energies using the fisher discriminant ratio (FDR). And the feature vectors through the linear discriminant analysis (LDA) transformation of the filterbank energies (FBE) and the MFCCs are implemented. An accuracy is measured by the GMM classifier. This paper shows that the FBE LDA-based GMM is a sufficiently distinct method for the pathological/normal voice classification, with a 96.6% classification performance rate. The proposed method shows better performance than the MFCC-based GMM with noticeable improvement of 54.05% in terms of error reduction.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.32 no.2
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• pp.75-80
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• 2021

Background and Objectives Functional aphonia refers to in which by presenting whispering voice and almost producing very high-pitched tensed voices are produced. Voice therapy is the most effective treatment, but there is a lack of consensus for application of voice therapy. The purpose of this study was to examine the vocal characteristics of functional aphonia and the effect of voice therapy applied accordingly. Materials and Method From October 2019 to December 2020, 11 patients with functional aphonia were treated using voice therapy which was processing three stages such as vocal hygiene, trial therapy, and behavioral therapy. Of these, 7 patients who completed the voice evaluation before and after voice therapy was enrolled in this study. By retrospective chart review, clinical information such as sex, age, symptoms, duration, social and medical history, process of voice therapy, subjective and objective findings were analyzed. Voice parameters before and after voice therapy were compared. Results In GRBAS study, grade, rough, and asthenic, and in Consensus Auditory-Perceptual Evaluation of Voice, overall severity, roughness, pitch, and loudness were significantly improved after voice therapy. In Voice handicap index, all of the scores of total and sub-categories were significantly decreased. In objective voice analysis, jitter, cepstral peak prominence, and maximum phonation time were significantly improved. Conclusion The voice therapy was effective for the treatment of functional aphonia by restoring patient's vocalization and improving voice quality, pitch and loudness.

• Speech Sciences
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• v.10 no.4
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• pp.201-219
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• 2003

Background: The perceptual assessment is generally performed by the voice specialist. The objective evaluation is performed in a voice laboratory. Research in voice laboratories has generated a variety of different objective tests and parameters. The perceptual evaluation is one of the most controversial topics in voice research. Review of literature reveals a wide variety of rating scales and reliability data fluctuating from study to study. Unfortunately, there is no widely accepted valid method for classifying voice disorders and assessing outcome after voice treatment. Objectives: The goals of this research were to identify important objective acoustic parameters of vocal quality, and to establish an objective and quantitative correlate of the perceived vocal quality. Materials and Methods : We evaluated the voice analyzed data from 122 dysphonic patients and 20 normal volunteers. A computerized speech lab. 4300B(CSL) was used to carry out the analysis of each voice sample. Results: Three dysphonia severity indices(DSI) were created using discriminant analysis. DSI is based on the weighted combination of the following selected set of acoustic parameters: absolute jitter(Jita in us), smoothed pitch period perturbation (sPPQ in %), amplitude perturbation quotient(APQ in %), soft phonation index(SPI), average fundamental frequency(Fo in Hz), lowest fundamental frequency(Flo in Hz), and smoothed amplitude perturbation quotient(sAPQ in %). The DSI, being the discriminating rule calculated by the logistic regression, consists of three equation based on statistically significant acoustic parameters. Three DSI were created to reflects best the degree of hoarseness as expressed by G from the GRBAS scale. The more positive this DSI is for a patient, the worse the vocal quality. The more it is negative, the better it is. The effect of sex is included implicitly in the DSI-1 and DSI-2, so that a separate DSI-1 and DSI-2 for males and females need not be used. The DSI is objective because no perceptual input is required for its calculation. Conculsion : This research demonstrates that the voice function values calculated from three different multivariate objective dysphonia severity indices are significantly associated with subjective voice assessments. These multivariate objective dysphonia severity indices may be appropriate for use in clinical trials and outcomes research on treatment effectiveness for voice disorders.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.31 no.1
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• pp.13-18
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• 2020

Background and Objective The purpose of this study is to report the effect of voice therapy using the voice reinforcement method (VRM) in patients with vocal nodules. It is one of the holistic voice therapy methods for improving vocal mechanisms. VRM includes not only direct and indirect voice therapy, but also trial therapy and self-practice. Composed of four stages: vocal hygiene education, relaxation, reinforcement, and generalization. Materials and Methods The subjects were 13 patients who were diagnosed with vocal nodules. Acoustic analysis, auditory perceptual assessment, K-VHI-10 and nodules size were compared before and after voice therapy. Voice therapy was conducted by speech-language pathologist and the mean number was 4.2. Results In acoustic analysis, Jitter, vF₀, vAm, Shimmer, NHR, and VTI were significantly decreased. F₀ was increased after voice therapy for women. 'Grade', 'Rough,' and 'Breathy' were significantly decreased in the GRBAS scale after voice therapy. In addition, K-VHI-10 and nodules size were significantly decreased. Conclusion VRM seems to be an effective voice therapy method in vocal nodules treatment. In VRM, especially, trial therapy is given motivation for vocal nodules treatments and self-practice has a continuous therapeutic effect in everyday life. VRM can be also applied to the voice therapy for other hyper-functional dysphonia.

• Journal of Pharmacopuncture
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• v.17 no.3
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• pp.57-61
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• 2014

Objectives: When a person speaks, voice problems usually include pain or discomfort and/or difficulties in terms of the pitch, the loudness and the quality of the voice. When patients with voice problems induced by stroke, Parkinson's disease, and systemic diseases involving the voice are examined, generally, of the Four Diagnoses (四診), a Diagnosis of Hearing can be used in current Korean medicine. The effects of acupuncture and herb medicine on voice problems have been reported for over 20 years. However, when it comes to improvements, objective and subjective evaluation methods need to be explained. Methods: Subjective methods for evaluating voice were studied through a literature search of old medicinal books containing Korean medicine diagnostics, and an objective evaluation method using Praat software is presented. Results: Korean medicine doctors analyze the patient's voice in clinical settings unconsciously on a daily basis. However, most voice diagnoses depend on the doctor's subjective evaluation. Voice qualities can be evaluated by using the Eight Principles (八綱), including Yin-Yang; the Five Elements (Phases); the Grade, Roughness, Breathy, Asthenic, Strained (GRBAS) score, and the Visual Analogue Scale (VAS) as subjective methods, and an acoustic analysis using the Praat program can be used as an objective method. Conclusion: A more complete voice examination can be achieved by using subjective and objective methods at the same time. For an objective explanation and management of patient's voice problems or systemic disorders, an objective method should be used in Korean medicine, which already has many subjective diagnostic methods. More research needs to be conducted, and more clinical evidence needs to be collected in the future.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.189-207
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• 2021

Voice interaction combined with artificial intelligence is poised to revolutionize human-computer interactions with the advent of virtual assistants. This paper is analyzing interactive elements of AI-based voice recognition services such as sympathy, assurance, intimacy, and trust on intention to use. The questionnaire was carried out for 284 smartphone/smart TV users in Korea. The collected data was analyzed by structural equation model analysis and bootstrapping. The key results are as follows. First, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy, and trust have positive effects on interactivity with the AI-based voice recognition service. Second, the interactivity with the AI-based voice recognition service has positive effects on intention to use. Third, AI-based voice recognition service characteristics such as interactional enjoyment and intimacy have directly positive effects on intention to use. Fourth, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy and trust have indirectly positive effects on intention to use the AI-based voice recognition service by mediating the effect of the interactivity with the AI-based voice recognition service. It is meaningful to investigate factors affecting the interactivity and intention to use voice recognition assistants. It has practical and academic implications.

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.99-106
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• 2017

Clinical data about vocal nodules have seldom been reported, even though vocal nodules are commonly diagnosed in outpatient speech and voice clinic. This study aims to investigate clinical characteristics of the patients who are diagnosed with vocal nodules. This study analyzed the data for 10 years from the 319 patients diagnosed with vocal nodules (45 males and 274 females with the mean age of 39.4 ranging from 2 to 83) in terms of gender, age, occupation, voice change initiation pattern, change with time, throat clearing, smoking history, type of voice abuse, acoustic analysis, maximum phonation time, GRBAS, and VHI. Thirteen patients (4.08%) had unilateral vocal nodule and 306 patients (95.9%) had bilateral vocal nodule, the majority of which had a pattern of asymmetry (73.9%). The glottal closure pattern was hourglass in 72.1% of patients, posterior chink in 17.9% of patients, and irregular in 7.9% of patients. The most common occupational category was professional voice users (43.4%). The voice abuse pattern included excessive talking in 96 patients (76.8%), loud voice in 78 (62.4%) patients, and excessive singing in 17 patients (21.6%). The patients showed worse scores in G, B, and S than in R and A for the GRBAS evaluation. The most recommended treatment for vocal nodules was voice therapy. The current clinical data will be helpful for treatment planning for the patients of vocal nodule.

• Convergence Security Journal
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• v.22 no.3
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• pp.79-86
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• 2022

Voice phishing is a cyber crime in which fake financial institutions, the Public Prosecutor's Office, and the National Police Agency are impersonated to find out an individual's Certification number and credit card number or withdraw a deposit. Recently, voice phishing has been carried out in a subtle and secret way. Analyzing the trend of voice phishing that occurred in '18~'21, it was found that there is a seasonality that occurs rapidly at a time when the movement of money is intensifying in the trend of voice phishing, giving ambiguity to time series analysis. In this research, we adjusted seasonality using the X-12 seasonality adjustment methodology for accurate prediction of voice phishing occurrence trends, and predicted the occurrence of voice phishing in 2022 using the ARIMA model.