Phonation Research Articles

Secure Electronics Medical Infrastructure for Healthcare 4.0: A Voice Identity Management-Based Approach

Securing Electronic Medical Records for Healthcare 4.0 is one of the prime requirements in the medical care service domains. Healthcare 4.0 refers to the evolution process of healthcare systems that leverage digital technologies, connectivity, and data-driven insights to provide more personalized and efficient care. With the increasing adoption of electronic healthcare records and the growing importance of data in the healthcare sector, ensuring the privacy of patient data becomes paramount. To ensuring the security for healthcare 4.0 in the current work a voice authentication-based system is devised. This enables the protection of electronic healthcare records (EHRs) in the association of healthcare 4.0. More precisely here the voice authentication is used as an additional layer of security for accessing and managing EHRs. The Voice authentication can also be categorized as the voice biometric. This is a technology that uses unique voice characteristics and patterns to verify the identity of individuals. The result establishes the innovative smart security arrangement for the Healthcare 4.0 using the voice authentication-based identity management infrastructure; and a modified version of asymmetric cryptosystem has been used inside the blockchain. The simulation outcome indicates better performance in the form of block generation time, block number, ensure the transaction, and minimize the latency of the transaction.

Clinical classification of memory and cognitive impairment with multimodal digital biomarkers.

Early detection of Alzheimer's disease and cognitive impairment is critical to improving the healthcare trajectories of aging adults, enabling early intervention and potential prevention of decline. To evaluate multi-modal feature sets for assessing memory and cognitive impairment, feature selection and subsequent logistic regressions were used to identify the most salient features in classifying Rey Auditory Verbal Learning Test-determined memory impairment. Multimodal models incorporating graphomotor, memory, and speech and voice features provided the stronger classification performance (area under the curve=0.83; sensitivity=0.81, specificity=0.80). Multimodal models were superior to all other single modality and demographics models. The current research contributes to the prevailing multimodal profile of those with cognitive impairment, suggesting that it is associated with slower speech with a particular effect on the duration, frequency, and percentage of pauses compared to normal healthy speech.

OTORHINOLARYNGOLOGICAL FINDINGS INRHEUMATOID ARTHRITIS (RA) PATIENTS

Rheumatoid arthritis is a persistent inflammatory illness that impairs joint function by destroying cartilage and causing synovitis. It is a debilitating illness that affects every joint in the body. Additionally, it manifests extra-articularly, impacting the auditory system as well as ENT manifestation. Regarding Laryngeal Symptoms, dysphonia or changes in voice quality can be caused by autoimmune illnesses in general and RA in particular. These changes can be caused by either functional or anatomical l modifications.Material and Method: 60 adults with rheumatoid arthritis classified into two groups the 1st group have disease duration less than or equal to 5 years and the 2nd group is more than 5 years. Disease activity was assessed using DAS 28 (Disease activity score). The entire patient underwent otoscopic examination of ears & Laryngeal examination as well asfull audiological evaluation including pure tone and speech audiometry and immetencemetryin the form of tympanometry and acoustic reflexes to assess middle function. Results: A total of 60 patients, 40 patients with a disease duration of less than or equal to five years (1st group). The 2nd group had disease duration of more than five years they were 20 patients. In RA patients the disease activity score was done using DAS-28 CRP, the first group with mean 5.3±1.3, the second group had a mean 5.9± 1.4. As for the Otorhinolaryngological findings we found that otalgia &myringo sclerosis and rhinogrnic findings there are no significant difference between the two groups. As regard laryngeal findings there are no significant difference between the two groups as regard edema, GERD and laryngeal swellings. Hearing loss was present in 16 (40%) patients in the first group and 17(85%) patients in the second group with highly significant difference between the two groups,there was direct correlation between disease duration °ree of hearing loss. Conclusion: our research revealed that the duration of RA had little bearing on laryngeal findings. On the other hand, the length of the illness had an effect on rhinogenic findings. Additionally, duration of RA and hearing test showed a direct association.

AUTOMATIC IDENTIFICATION OF DYSPHONIAS USING MACHINE LEARNING ALGORITHMS

Dysphonia is a prevalent symptom of some respiratory diseases that affects voice quality, even for prolonged periods. For its diagnosis, speech-language pathologists make use of different acoustic parameters to perform objective evaluations on patients and determine the type of dysphonia that affects them, such as hyperfunctional and hypofunctional dysphonia, which is important because each type requires a different treatment. In the field of artificial intelligence this problem has been addressed through the use of acoustic parameters that are used as input data to train machine learning and deep learning models. However, its purpose is usually to identify whether a patient is ill or not, making binary classifications between healthy voices and voices with dysphonia, but not between dysphonias. In this paper, harmonic-to-noise ratio, cepstral peak prominence-smoothed, zero crossing rate and the means of the Mel frequency cepstral coefficients (2-19) are used to make multiclass classification of voices with euphony, hyperfunction and hypofunction by means of six machine learning algorithms, which are: Random Forest, K nearest neighbors, Logistic regression, Decision trees, Support vector machines and Naive Bayes. In order to evaluate which of them presents a better performance to identify the three voice classes, bootstrap.632 was used. It is concluded that the best confidence interval ranges from 87% to 92%, in terms of accuracy for the K Nearest Neighbors model. Results can be implemented in the development of a complementary application for the clinical diagnosis or monitoring of a patient under the supervision of a specialist.

Modal Versus Creaky Filler Particles in Romanian Connected Speech

This paper represents a preliminary acoustic analysis of filler particles in terms of voice quality (i.e., modal vs. creaky phonation). The main research questions addressed in this study revolve around which particular voice parameters are indicative of (non)modal phonation of fillers used by healthy speakers of Standard Romanian, and whether the function of the filler particle varies with different voice qualities. The analysis is carried out on Romanian connected speech data extracted from the Ro-Phon corpus (non-pathological speech), an open-access linguistic resource developed during our postdoctoral research project financed by UEFISCDI (2020 – 2022).

A Synthetic Voice for an Assistive Conversational Agent: A Survey to Discover Italian Preferences regarding Synthetic Voice’s Gender and Quality Level

Based on a previous investigation, a quantitative study aimed to identify user’ preferences towards four synthetic voices of two different quality levels (classified through the sophistication of the synthesizer: low vs. high) is proposed. The voices administered to participants were developed considering two main aspects: the voice quality (high/low) and their gender (male/female). 182 unpaid participants were recruited for the study, divided in four groups according to their age, and therefore classified as adolescents, young adults, middle-aged, and seniors. To collect data regarding each voice, randomly audited by participants, the shortened version of the Virtual Agent Voice Acceptance Questionnaire (VAVAQ) was exploited. Outcomes of the previous study revealed that the voices of high quality, regardless of their gender, received a higher acclaim by all participants examined rather than the corresponding two voices assessed as lower quality. Conversely, findings of the current study suggest that the four new groups of participants involved agreed in showing their strong preference towards the high-quality voice gendered as female compared to all the other considered voices. Regarding the two voices gendered as male, the high-quality one was considered as more original and capable to arouse positive emotional states than the low-quality one. Moreover, the high-quality male voice was judged as more natural than the female low-quality one. Results provide some insights for future directions in the user experience and design field.

Temporal and Spectral Models as Correlates to Auditory-Perceptual Judgments of Overall Severity and Listener Comfort in Tracheoesophageal Voice.

This study pursued two objectives: (1) to determine the potential association between listener (n = 51) judgments of 20 male tracheoesophageal speaker samples for two auditory-perceptual dimensions of voice, overall severity (OS) and listener comfort (LC); and (2) to assess the temporal and spectral acoustic correlates for these auditory-perceptual dimensions. Three separate correlation analyses were performed to evaluate the association between OS and LC. First, scores of OS and LC from all listeners were pooled together, and then the correlation between OS and LC was computed. Second, scores of OS and LC were averaged over all listeners to derive a single estimate of OS and LC for each TE speaker sample; the correlation between the average OS and LC was then computed. Third, listener-to-listener variability in the association between OS and LC was evaluated by computing the correlation between OS and LC scores from each listener across all TE samples. Finally, two stepwise multiple regression models were created to relate the average LC score to spectral and temporal variation in the acoustic signal. While the pooled OS and LC scores had a moderate positive correlation (r = 0.66, p < 0.00001), the averaged OS and LC exhibited a near perfect positive correlation (r = 0.99, p < 0.00001). The significant differences between the pooled and averaged scores were explained by significant listener-to-listener variability in the association between OS and LC. OS and LC scores from 5 listeners had non-significant correlations, 10 had moderate correlations (r < 0.7), 35 listeners had high correlations (0.7 < r < 0.9), and 1 listener had a very high correlation (r < 0.9 < 1). Finally, the acoustic models created based on the spectral and temporal variations in the signal were able to account for 87.7% and 61.8% of variation in the average LC score. The strong correlations between OS and LC suggest that LC may, in fact, provide a more comprehensive auditory-perceptual surrogate for the voice quality of TE speakers. Although OS and LC are distinct conceptual dimensions, LC appears to have the advantage of assessing the social impact and potential communication disability that may exist in interactions between TE speakers and listeners.

Louise Erdrich’s The Plague of Doves - A Study Using Bakhtin’s Dialogism

The aim of this paper is to advance the theoretical aspect of Bhaktin’s Dialogism in the Native American literature with special reference to the novel The Plague of Doves. By closely examining the text, the study finds the presence of the dialogical elements in the novel. Additionally, it examines the character voices that are blending together to generate dialogic forms. Instead of showcasing their own strength, the voices allowed other voices to emerge and take on unique qualities while they persisted until the conclusion of the narrative.

Accuracy Analysis of the Multiparametric Acoustic Voice Indices, the VWI, AVQI, ABI, and DSI Measures, in Differentiating between Normal and Dysphonic Voices.

The study aimed to investigate and compare the accuracy and robustness of the multiparametric acoustic voice indices (MAVIs), namely the Dysphonia Severity Index (DSI), Acoustic Voice Quality Index (AVQI), Acoustic Breathiness Index (ABI), and Voice Wellness Index (VWI) measures in differentiating normal and dysphonic voices. The study group consisted of 129 adult individuals including 49 with normal voices and 80 patients with pathological voices. The diagnostic accuracy of the investigated MAVI in differentiating between normal and pathological voices was assessed using receiver operating characteristics (ROC). Moderate to strong positive linear correlations were observed between different MAVIs. The ROC statistical analysis revealed that all used measurements manifested in a high level of accuracy (area under the curve (AUC) of 0.80 and greater) and an acceptable level of sensitivity and specificity in discriminating between normal and pathological voices. However, with AUC 0.99, the VWI demonstrated the highest diagnostic accuracy. The highest Youden index equaled 0.93, revealing that a VWI cut-off of 4.45 corresponds with highly acceptable sensitivity (97.50%) and specificity (95.92%). In conclusion, the VWI was found to be beneficial in describing differences in voice quality status and discriminating between normal and dysphonic voices based on clinical diagnosis, i.e., dysphonia type, implying the VWI's reliable voice screening potential.

Hybrid AI-based Voice Authentication

Biometric authentication systems reveal individuals' physical or behavioral uniqueness and identify them by comparing them with existing records. Today, many biometric recognition systems, such as fingerprint reading, palm reading, and face reading, are being studied and used. The human voice is also among the techniques used for this purpose. Due to this feature, the human voice performs secure transactions and authentication in various fields. Based on these voice features, we used a dataset of 66,569 voice recordings. The voice recordings were revised to include six sentences of at least six words each from 24 different people to get the maximum benefit from the dataset. The voices in the reduced dataset were labeled as sentences belonging to the same person and sentences belonging to different people and converted into matrix form. A biometric recognition study resulted in a correlation score of 0.88. As a result of these processes, the feasibility of a voice biometric recognition system with artificial intelligence has been demonstrated.

Context effects on duration, fundamental frequency, and intonation in human-directed domestic cat meows

In this study, we investigated the prosody of domestic cat meows produced in different contexts. Prosodic cues – i.e., variation in intonation, duration, voice quality and fundamental frequency – in humans as well as in nonhuman animals carry information about idiosyncratic traits of the signaller, including sex, age, and physical and mental state. The duration, fundamental frequency (F0) and intonation in a sample of 969 meows recorded in seven different contexts (i.e., cuddle, door, food, greeting, lifting, play, cat carrier) were analysed using linear mixed effects regression and generalized additive models. In this, we controlled for cat age and sex, as meows produced by old cats had lower mean F0 than those produced by young cats, and female cats produced meows with higher mean F0 than male cats. We found significant effects of context on duration and mean F0, but not on F0 range. Furthermore, the results showed that the intonation of meows produced by cats in a cat carrier displayed a falling pattern, while that of meows produced in cuddle and door contexts was relatively level, and that of meows produced in the other contexts consisted of combinations of rising and falling. The average slope of meows produced in cat carrier and play contexts was negative, while that of meows produced in the other contexts was positive. We argue that this prosodic variation reflects the cats’ mental or emotional state, because of valence and arousal differences associated with the various contexts that were included in the study. Further studies will need to confirm this. In addition, we also plan additional analyses of spectral and voice quality parameters in meows and other cat vocalisation types.

An Intelligent Framework Based on Deep Learning for Online Quran Learning during Pandemic

The COVID-19 pandemic influenced the whole world and changed social life globally. Social distancing is an effective strategy adopted by all countries to prevent humans from being infected. Al-Quran is the holy book of Muslims and its listening and reading is one of the obligatory activities. Close contact is essential in traditional learning system; however, most of the Al-Quran learning schools were locked down to minimize the spread of COVID-19 infection. To address this limitation, in this paper, we propose a novel system using deep learning to identify the correct recitation of individual alphabets, words from a recited verse and a complete verse of Al-Quran to assist the reciter. Moreover, in the proposed approach, if the user recites correctly, his/her voice is also added to the existing dataset to leverage proposed approach effectiveness. We employ mel-frequency cepstral coefficients (MFCC) to extract voice features and long short-term memory (LSTM), a recurrent neural network (RNN) for classification. The said approach is validated using the Al-Quran dataset. The results demonstrate that the proposed system outperforms the state-of-the-art approaches with an accuracy rate of 97.7%. This system will help the Muslim community all over the world to recite the Al-Quran in the right way in the absence of human help due to similar future pandemics.

POSSIBILITIES OF IMPROVING THE VOICE SERVICES QUALITY IN 5G NETWORKS

Background. The introduction of fifth-generation (5G) networks creates new opportunities for fast and continuous data exchange, but there are still some problems with the quality of voice services in such networks. With the rapid development of technology and the further spread of 5G, there is a need to understand the impact of key aspects of 5G on voice quality. This requires research that can systematically analyse the features of 5G networks that affect the quality of voice services.&#x0D; Objective. Identification of ways to improve the quality of voice services in 5G networks. Assessment of key indicators of voice service quality in 5G networks. Determination of the best option for the gradual transition to the Standalone mode and the use of VoNR technology in the fifth generation networks.&#x0D; Methods. Analysis of factors affecting the quality of voice services in fifth-generation networks. Analysis of well-known publications on the implementation of 5G networks. Comparison of the implementation of Non-Standalone and Standalone modes in the 5G network. Testing of the modern EVS codec, which provides an opportunity to improve the customer experience.&#x0D; Results. Confirmation that 5G networks can significantly improve the quality of voice services compared to previous mobile communication technologies such as 4G and 3G. Certain factors that may affect the quality of voice services and require additional attention when planning and deploying 5G networks are identified. The optimal steps for the transition to the Standalone mode and the use of VoNR technology in fifth-generation networks are determined. The main differences in the QoS architecture between LTE and 5G are identified, and the purpose of DRB flows for separating traffic types and services is established.&#x0D; Conclusions. It has been confirmed that 5G networks can significantly improve the quality of voice services compared to previous technologies such as 4G and 3G. This is possible due to the broadband capabilities of 5G networks, improved data transmission, low latency, the use of an advanced EVS codec and reduced response time. However, certain factors, such as network coverage, optimisation level and traffic characteristics, can affect the quality of voice services and require additional attention when planning and deploying 5G networks. The QoS management architecture consists of QoS flows, which allow separating packet assignment to flows (managed by the CN) from the assignment of DRB flows (managed by the RAN). As 5G networks are being rolled out gradually, it is important to properly integrate the 5G domain into the existing telecoms provider's network. The transition from Non-Standalone to Dual connectivity is a necessary step for the implementation of VoNR technology in Standalone mode. Using the modern EVS codec allows not only improving the customer experience, but also introducing new voice services.

Comparing dysphonia severity index, objective, subjective, and perceptual analysis of voice in patients with multiple sclerosis and healthy controls

BackgroundImpairments in voice quality in Multiple Sclerosis (MS) have recently been investigated and different results were found. A voice-centered multidimensional assessment protocol with patient-reported outcome measures was conducted to evaluate all the aspects of the voice changes. ObjectivesThe study aimed to compare the objective, subjective, and perceptual measures of voice between the people with MS and the healthy control group. MethodsA total of 128 participants, including 64 people with MS age, and gender-matched healthy controls were enrolled in the study. Subjective, objective, and auditory-perceptual voice assessments of the participants were performed. The auditory-perceptual evaluation was performed with GRBAS. The Dysphonia Severity index was computed for both groups. All the participants completed the Turkish version of The Voice Handicap Index-10 (VHI-10) and the Voice-Related Quality of Life (VRQoL). ResultsAcoustic and aerodynamic parameters of voice were found significantly different for both males and females between the MS and control group. DSI was found significantly different for both males and females in the MS group compared to the control group (p<0.05). All components of the GRBAS scale were significantly higher in the MS group (p<0.001). Using a multivariate regression model, it was determined that age, gender, EDSS score, number of MS attacks, and disease duration did not affect the DSI. The overall VHI-10 score was higher in the MS group (median=1.0 range= 0–28) and lower in the control group (median=0 range= 0–4). The mean VRQoL was lower in the MS group (median=95 range= 62.5–100) than in controls (median=100 range= 85–100) (p<0.001). ConclusionOur results indicated that people with MS have significant differences in acoustic and aerodynamic parameters of voice compared to healthy individuals. A significant number of persons with MS are aware that their voice problem affects their quality of life. People with MS must be monitored for voice changes and a multidimensional voice assessment protocol should be implemented.

Impact of a Three-Week Workplace Vocal Health Promotion Program on a Teacher and Students' Voice Parameters

Objective. To determine the effect on voice parameters in pupils and their teacher of a three-week Workplace Vocal Health Promotion Program (WVHPP) in a school setting. Methods. Longitudinal study with a design phase and a pilot phase. Voice recordings of connected speech were used to collect information on voice functioning before and after the implementation of the program. The workplace vocal health promotion program was implemented with two purposes: (1) to reduce noisy conditions inside the classrooms that may cause loud voice production, which has been found associated with voice disorders among teachers and students and (2) to increase awareness about the relationship between noise and voice inside the classrooms. Results. The WVHPP was found to be statistically associated with a decrease in the fundamental frequency, standard deviation of the fundamental frequency, sound pressure levels, and SPL standard deviation among both pupils and their teacher. However, there was no statistically significant effect on cepstral peak prominence smoothed. Conclusion. The three-week WVHPP was found to have a significant impact on several acoustic parameters, such as the fundamental frequency and sound pressure levels. These findings highlight the potential of the WVHPP as an effective intervention for improving the vocal health of both teachers and students. However, the lack of a significant effect on cepstral peak prominence smoothed suggests that further research is needed to fully understand the impact of the WVHPP on voice quality.

A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection

Voice is an essential component of human communication, serving as a fundamental medium for expressing thoughts, emotions, and ideas. Disruptions in vocal fold vibratory patterns can lead to voice disorders, which can have a profound impact on interpersonal interactions. Early detection of voice disorders is crucial for improving voice health and quality of life. This research proposes a novel methodology called VDDMFS [voice disorder detection using MFCC (Mel-frequency cepstral coefficients), fundamental frequency and spectral centroid] which combines an artificial neural network (ANN) trained on acoustic attributes and a long short-term memory (LSTM) model trained on MFCC attributes. Subsequently, the probabilities generated by both the ANN and LSTM models are stacked and used as input for XGBoost, which detects whether a voice is disordered or not, resulting in more accurate voice disorder detection. This approach achieved promising results, with an accuracy of 95.67%, sensitivity of 95.36%, specificity of 96.49% and f1 score of 96.9%, outperforming existing techniques.

The Minimal Important Difference of Acoustic Voice Quality Index in the Treatment of Voice Disorders.

The acoustic voice quality index (AVQI) is a reliable tool that objectively assesses dysphonia levels using six acoustic parameters. Despite its high criterion-related concurrent validity, diagnostic accuracy, and minimal detectable change derived from test-retest reliability, the minimal important difference (MID) of the AVQI has not been tested before. This study aimed to estimate the MIDs of AVQI for improvement audibly perceived by clinicians and self-reported improvement by patients. A retrospective study was conducted on 110 patients who received treatment for voice disorders. Patients completed AVQI and Voice Handicap Index-10 (VHI-10) questionnaires before and after the therapy. The MIDs of the AVQI were estimated using the anchor of either auditory-perceptual judgment of total dysphonia levels by clinicians or the VHI-10 questionnaire by patients. A distribution-based approach was also used to complement the results. First, using the auditory-perceptual anchor, a decrease of 0.95 in the AVQI was estimated as the MID for clinicians' perception, as a result of the receiver operating curve. Then, using the patient-reported anchor, an improvement of 1.36 in the AVQI was estimated as the MID for patients' voice-related disability. The distribution-based approach also ensured the anchor-based results of both the MIDs. The AVQI is a reliable and valid tool for evaluating voice quality, and a 0.95 decrease in the AVQI represents a meaningful improvement for clinicians' perception, whereas a 1.36 decrease in the AVQI influences patients' self-reported disability. This study contributes to understanding the minimal change necessary for clinicians to make informed decisions and ensure patient satisfaction. 3 Laryngoscope, 134:2805-2811, 2024.

Rehabilitation Treatment Specification System for Voice Therapy: Application to Everyday Clinical Care.

Rehabilitation intervention descriptions often do not explicitly identify active ingredients or how those ingredients lead to changes in patient functioning. The Rehabilitation Treatment Specification System (RTSS) provides guidance to identify the critical aspects of any rehabilitation therapy and supported the development of standardly named ingredients and targets in voice therapy (Rehabilitation Treatment Specification System for Voice Therapy [RTSS-Voice]). This study sought to test the content validity of the RTSS-Voice and determine if the RTSS-Voice can be used to identify commonalities and differences in treatment (criterion validity) across clinicians in everyday clinical practice. Five speech-language pathologists from different institutions videotaped one therapy session for 59 patients diagnosed with a voice or upper airway disorder. Specifications were created for each video, and iterative rounds of revisions were completed with the treating clinician and two RTSS experts until consensus was reached on each specification. All 59 sessions were specified without the addition of any targets or ingredients. There were two frequent targets: (a) increased volition and (b) decreased strained voice quality. There were three frequent ingredients: (a) information regarding the patient's capability and motivation to perform a therapeutic behavior, (b) knowledge of results feedback, and (c) opportunities to practice voicing with improved resonance and mean airflow. Across sessions treating vocal hyperfunction, there was large variability across clinicians regarding the types and number of treatment components introduced, types of feedback provided, and vocal practice within spontaneous speech and negative practice. The RTSS and the RTSS-Voice demonstrated strong content validity, as they comprehensively characterized 59 therapy sessions. They also demonstrated strong criterion validity, as commonalities and differences were identified in everyday voice therapy for vocal hyperfunction across multiple clinicians. Future work to translate RTSS principles and RTSS-Voice terms into clinical documentation can help to understand how clinician and patient variability impacts outcomes and bridge the research-practice gap. https://doi.org/10.23641/asha.24796875.

3D-exoscopic microlaryngoscopy in phonosurgery for glottic insufficiency

PurposeWe hypothesized that using a 3D-exoscope (3Dex) in microlaryngoscopic phonosurgery is non-inferior to using a standard operating microscope (OM). To compare the above, we utilized a 3Dex and an OM for microlaryngoscopic vocal fold augmentation with autologous fat in patients with glottic insufficiency and compared the procedure itself and the long-term impact of vocal fold augmentation on subjective and objective voice parameters in both groups.Methods36 patients with glottic insufficiency received microlaryngoscopic laryngeal augmentation with autologous fat. A 3Dex was utilized in 24 cases for visualization and compared to twelve cases in which an OM was used. Voice parameters were evaluated over a period of twelve months.ResultsComparison of operation time and voice parameters between the 3Dex and OM groups did not reveal significant differences. Significant improvement of mean voice quality in all parameters excluding roughness was observed at 3 and 6 months followed then by a slight decrease of voice quality parameters between the 6 and 12 months interval in both groups.ConclusionOur findings indicate no difference concerning operation time and outcome between the use of a 3Dex and an OM in phonosurgery. Our results highlight a significant voice improvement after vocal fold augmentation with autologous fat in glottic insufficiency mediated dysphonia. The smaller viewing system, better ergonomics for the primary surgeon and the assistant and a direct view for the entire surgical team make a 3Dex an interesting alternative for visualization in microlaryngoscopic phonosurgery.

예비 국어교사와 현직 국어교사의 음성 특성 분석

Objectives The purpose of this study is to analyze the voice characteristics of pre-service and in-service Korean language teachers to find ways to systematically manage their voice problems.&#x0D; Methods To this end, this study investigated 55 pre-service and 47 in-service teachers' perceptions of voice symptoms and voice problems(VHI), and collected voices and conducted acoustic analysis to understand the sta-tus of voice problems they are experiencing.&#x0D; Results First, both pre- and in-service teachers are experiencing voice problems, but the rate of recognizing them as “problems” is low. Second, in-service teachers tended to recognize cause of voice problems in relation to classes. Third, VHI of both pre- and in-service teachers are low and the physical category had the highest VHI among three categories. Fourth, in-service teachers showed a higher rate of Shimmer abnormalities than pre-service teachers, and 50% of female teachers showed F0 abnormalities. Fifth, pre-service teachers tend to be more sensitive to their voice problems than in-service teachers, but the rate of who have actual voice problems is higher for in-service teachers.&#x0D; Conclusions In order to systematically manage the voice problem of Korean teachers, it is necessary to periodi-cally and continuously educate teachers on voice problems and ways to manage and treat them through teacher training courses, teacher retraining, or training, and active support from the Ministry of Education or the Office of Education is needed.