A Comparative Acoustic Study of Voice Rehabilitation After Total Laryngectomy / 대한이비인후과학회지

BACKGROUND AND OBJECTIVES: Acoustic parameters of maximal phonation time, sound intensity, fundamental frequency, voice range, jitter and shimmer were analyzed in order to evaluate voice quality and differences among esophageal speech (ES), tracheoesophageal shunt speech (TES), pneumatic aid speech (PA), electrolaryngeal speech (EL) according to phonetic rehabilitation methods in 16 cases of laryngectomees. MATERIALS AND METHODS: We acquired acoustic data on alaryngeal voice by different methods, and analysed each of those using specially designed programs (Laryngeal analyser V1.0 base on Matlab V5.0). RESULTS: Maximal phonation time was significantly longer in TES voice and PA speech than in ES voice (p<0.05). Jitter and shimmer were significantly regular and stable in the EL and PA speech than in the ES and TES voice (p<0.05). Voice range was significantly wider in TES voice and PA speech than in EL and ES voice (p<0.05). In two cases capable of bi-modal speech of ES and TES voice, maximal phonation time was longer with wider voice range in TES voice than in ES voice. Jitter and shimmer were regular and stable in ES voice than in TES voice. CONCLUSION: PA speech displays phonetically more natural laryngeal speech than other rehabilitation methods. But this methods is inconvenient and cosmetically unacceptable, because patients have to bite intraoral vibrator in the patient's mouth. So, we recommend TES voice rather than ES voice, without the use of speech-making device such as EL and PA speech.

The Vocal Tract and Speech Intelligibility of Tracheoesophageal Shunt Patients after Total Laryngectomy / 대한이비인후과학회지

BACKGROUND AND OBJECTIVES: In this paper, rehabilitation of voice after total laryngectomy has been suggested through the correct estimation and simulation of patients' vocal tract. Material and Methods: The author studied the shape of vocal tract during the phonation of five Korean vowels /u, o, a, e, i/ in tracheoesophageal shunt patients by magnetic resonance images (MRI). The same vocal tract was determined in each vowels from MRI. First, speech data produced by them were analyzed and also checked for speech intelligibility. Then the author tried to synthesize vowels from the vocal tract area of each vowels and from the expanded pharyngeal section of the vocal tract. RESULTS: The obtained results were as follows: 1) The sounds of /a/, /e/, /i/ were similar to natural sounds in actual patients' speech. The sound of /o/ was heard as /sigma/. The sound of /u/ was heard as strained /u/. 2) The synthesized vowels of /a/, /e/ from MRI were heard as natural sounds. The sounds of /u/, /o/, /i/ were heard as other sounds. 3) The synthesized vowel by the expanded pharyngeal section of 3 times in vowel /o/ was more naturally heard than that of 2 times. The synthesized vowel from Formfrek was more naturally heard than that from AreatoFormant. CONCLUSION: In conclusion, some of the synthesized sounds from MRI disagrees with the actual sounds produced by the subjects. This could be best identified by the synthesis from the area data. Future MRI studies should consider this problem for more accurate measurements. Also, pharyngeal areas with varied sizes should be experimented to secure better speech output because the correct shapes of vocal tract ensures correct vowel pronunciation.

Acoustic Parameters for the Early Detection and Differential Diagnosis of Pathologic Voice / 대한이비인후과학회지

BACKGROUND AND OBJECTIVES: The survival rate of laryngeal cancer has improved in recent day. But in case of advanced cancer, radical destructive surgery is required for survival. So early detection of laryngeal cancer prevent from this disastrous condition. In this point of view, mass screening test for early detection of laryngeal cancer is necessary. Screening tests using voice has many advantages of being simple, non invasive, and requiring less space. In this system, the most important factor is the selection of acoustic parameters to be used in voice analysis. Thus authors studied the acoustic parameters that can differentiate normal, benign, malignant laryngeal diseases by an acoustic analyzing system and we also checked the availability of parameters. MATERIALS AND METHODS: We evaluated the voice analyzed data from 25 laryngeal malignancy patients, 33 benign laryngeal disease patients, 35 normal control who visited PNUH otolaryngology department from October 1996 to May 1998. A computerized speech lab. 4300B (CSL) was used to carry out the analysis of each voice sample and statistical analysis, ANOVA. Canonical analysis and cumulative frequency curve were used. RESULTS: The statistically significant parameters that can differentiate normal and malignant laryngeal disease groups were 15 parameters and can differentiate normal and benign laryngeal disease group were 9 parameters and that can differentiate benign and malignant laryngeal disease group were 7 parameters. CONCLUSION: We consider that these parameters and detection programs may be effective in development of a screening system using voice only. Developing diagnostic tools and programs would need further study of phonetics and voice engineering.

Digital Analysis of Asthmatic Cough Sounds / 소아알레르기및호흡기학회지

PURPOSE: Cough is a frequent symptom in bronchial asthma. Acoustic digital analysis of cough has been reported using digital signal processing techniques. Differences between asthmatic and control cough sounds are presented. The main purpose of this study was to examine whether overall spectral energy and the visual observation of the fine details of the cough spectrographs, explain the differences in cough between normal subjects and asthmatic patients. METHODS: We presented data from 7 asthmatic patients and 8 non-asthmatic subjects using a new method of acoustic analysis. Cough sound was digitalized at a sampling rate of 5 kHz. Individual coughs were divided into two or three phases, presents the data of RMS (Root Mean Square), duration, RMS in the frequency band. Factor analysis and iogistic regression analysis were performed to identify groups of variables. RESULTS: Duration of cough was longer in asthmatics cough. The number of additional cough sounds showed no difference. RMS of cough in total cough and 2nd phase cough was stronger for asthmatics cough. Energy of frequency band is significantly different in 1,000-1,500 Hz, 1,500-2,000 Hz, 5,000-5,500 Hz, 5,500-6,000 Hz, 6,000-6,500 Hz, 9,000-9,500 Hz at total phase, 0-500 Hz, 1,000-1,500 Hz, 2,000-2,500 Hz, 5,000-5,500 Hz, 6,000-6,500 Hz, 9,000-9,500 Hz at 1st phase. Factor analysis and logistic regression analysis for the two groups provoded a classification table of 96.3% of sensitivity and 86.0% of specificity. CONCLUSION: We provided a new approach to the analysis of cough sounds. Significant differences were found between asthmatic and non-asthmatic cough sounds. It has potential as a tool with which to study the pathophysiology of cough and diagnosis the respiratory disease.