Acoustic Analysis of Nasal and Oral Speech of Normal versus Cleft Lip and Palate Asharani Neelakanth 1 Mrs. Umarani K. 2

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IJSRD - International Journal for Scientific Research & Development Vol. 3, Issue 05, 2015 ISSN (online): 2321-0613 Acoustic Analysis of Nasal and Oral Speech of Normal versus Cleft Lip and Palate Asharani Neelakanth 1 Mrs. Umarani K. 2 1 M.Tech. Student 2 Associate Professor 1,2 Department of Instrumentation Technology 1,2 Sri Jayachamarajendra College of Engineering, Mysore 570006 Abstract Analysis of acoustics and speech is an important prerequisite to understanding of speech perception of an individual. Nasal and oral sounds have to be understood clearly to understand speech effectively. The present study was aimed at finding the severity of nasal and oral sounds of cleft lip and palate by comparing normal speech sounds and the speech of cleft lip and palate subjects. Speech is an acoustic signal which results from three components of voice production: voiced sound, resonance, and articulation. Acoustic resonances in the vocal tract can produce peaks in the spectral envelope of the output sound. In speech science, the word formant is used to describe either the spectral peak or the resonance that gives rise to it. These formant frequencies are obtained from Welch s power spectral density estimate method using MATLAB. Statistical significance test is carried out to compare the speech of both normal and CLP subjects. The results of the statistical analysis are utilized to find the severity in CLP. The speech samples of different Kannada syllables of normal as well as cleft lip and palate subjects are used. Eight oral and two nasal syllables of seven normal and seven abnormal persons are used and compared. These helps in classifying the severity of speech disorder as mild, moderate, moderately and. This provides information about atypical consonant productions, abnormal nasal resonance, abnormal nasal airflow, altered laryngeal voice quality, nasal or facial grimaces and velopharyngeal dysfunction which helps in speech therapy and speech intelligibility. Key words: Cleft Lip and Palate, Welch's Power Spectral Density, Formant Frequencies I. INTRODUCTION Cleft is a separation or space between parts that are normally joined, thus interrupting the continuity of the structure. Although orofacial clefts can be acquired through various traumas, the vast majority of those of the lip and/or hard and soft palates are due to congenital failures of the structures to join. A. Cleft Lip A cleft of the lip involves only soft tissue and extends through the red part of the lip or vermillion border, into the upper portion of the upper lip toward the nostril. If the cleft is unilateral, it commonly occurs on the left side. Patient may have a short columella, which is the strip of tissue between the base and the tip of the nose. B. Cleft Palate The palate serves as the partition between the nasal and oral cavities. The anterior two-third of the palate make up the hard palate, commonly referred to as the roof of the mouth. The soft palate or velum consists of the posterior one-third of the palate. Isolated cleft palate, without cleft lip, may include the entire hard palate posterior to the incisive foramen and the soft palate; it may involve only a small portion of the posterior part of the soft palate; or it may between these two extremes. Cleft lip (cheiloschisis) and cleft palate (palatoschisis) are variations of a type of clefting congenital deformity caused by abnormal facial development during gestation with a prevalence of about one in 750 to 900 births. Clefts can also affect other parts of the face, such as the eyes, ears, nose, cheeks, and forehead. Research has shown that during the early preschool years (ages 3 5), children with cleft lip and/or cleft palate tend to have a self-concept that is similar to their peers without a cleft. However, as they grow older and their social interactions increase, children with clefts tend to report more dissatisfaction with peer relationships and higher levels of social anxiety. Experts conclude that this is probably due to the associated stigma of visible deformities and possible speech impediments. Children who are judged as attractive tend to be perceived as more intelligent, exhibit more positive social behaviours, and are treated more positively than children with cleft lip and/or cleft palate. Children with clefts tend to report feelings of anger, sadness, fear, and alienation from their peers, hence cleft lip/palate may impact on individual s self-esteem, social skills and behaviour. It may leads to psychological problems. Therefore investigation of severity in cleft lip and palate gaining importance. II. SPEECH PRODUCTION A simplified view of speech production is given in Fig.1, where the speech organs are divided into three main groups: the lungs, larynx, and vocal tract. Fig. 1: Human vocal apparatus used to produce speech The spoken word results from three components of speech production: voiced sound, resonance, and articulation. The basic sound is produced by vocal fold vibration. This is frequently described as a "buzzy" sound, All rights reserved by www.ijsrd.com 327

which is amplified and modified by the vocal tract resonators (the throat, mouth cavity, and nasal passages). The resonators produce a person's recognizable voice. The vocal tract articulators (the tongue, soft palate, and lips) modify the voiced sound. The articulators produce recognizable words. Voice depends on Vocal Fold Vibration and Resonance. Voice production involves a three-step process. 1) A column of air pressure is moved towards the vocal folds: Air is moved out of the lungs and towards the vocal folds by coordinated action of the diaphragm, abdominal muscles, chest muscles, and rib cage 2) Vocal fold vibration sequence of vibratory cycles: Vocal folds are moved to midline by voice box muscles, nerves, and cartilages. The vibratory cycle occurs repeatedly; one vibratory cycle is as follows: Column of air pressure opens bottom of vocal folds Column of air continues to move upwards, now towards the top of vocal folds, and opens the top The low pressure created behind the fast-moving air column produces a "Bernoulli effect" which causes the bottom to close, followed by the top Closure of the vocal folds cuts off the air column and releases a pulse of air New cycle repeats 3) Vocal tract resonators and articulators: The nose, pharynx, and mouth amplify and modify sound, allowing it to take on the distinctive qualities of voice III. POWER SPECTRAL DENSITY The power spectral density (PSD) of the signal, when multiplied by the appropriate factor, describes the power contributed to the wave, by a frequency, per unit frequency. Power spectral density is commonly expressed in watts per hertz (W/Hz). It makes more sense to define a power spectral density (PSD), which describes how the power of a signal or time series is distributed over the different frequencies. In this paper PSE has been performed for various speech samples using Welch Method. Welch method is nonparametric method that include the periodogram that have the advantage of possible implementation using the fast Fourier Transform. Welch method in which the power of any input is guesstimation at different frequencies. It is an improvement on the periodogram spectrum estimation method where signal to noise ratio is high and reduces noise in the estimated power spectra in exchange for reducing the frequency resolution. (a) Normal case A. case Fig.2 MATLAB result of PSD estimate of syllable ra for (a) normal and (b) abnormal case B. Normal case C. case Fig.3 PSD estimate of nasal sound na for (a) normal and (b) abnormal case IV. FORMANT FREQUENCIES Formants are defined by Gunnar Fant. In acoustics generally formants are defined as: "a range of frequencies (of a complex sound) in which there is an absolute or relative maximum in the sound spectrum". In speech science a formant is used to mean an acoustic resonance of the human vocal tract. Thus, in phonetics, formant can mean either a resonance or the spectral maximum that the resonance produces. Formants are often measured as amplitude peaks in the frequency spectrum of the sound, using PSD estimation. This gives an estimate of the vocal tract resonances. Formants are the distinguishing or meaningful frequency components of human articulation and of singing. By definition, the information that humans require to distinguish between consonants can be represented purely quantitatively by the frequency content of the consonant All rights reserved by www.ijsrd.com 328

sounds. The Fig.2 and Fig.3 shows the formant frequencies F1,F2 and F3 for syllable ra and na. V. METHODOLOGY The method to classify the severity of Kannada oral and nasal speech samples for cleft lip and palate is explained using Fig.4. A. Block Diagram Fig. 4: Block diagram Nasal and oral sounds of Kannada language are recorded through the microphone from normal and abnormal individuals. Power spectral density is estimated with the help of Welch method by using MATLAB tool to find thee Syllable Formants frequencies Ka F2 Normal Ga F2 Normal Cha F2 Normal Ja F2 Normal Pa F2 Normal F3 formant frequencies F1, F2 and F3 as shown in Fig.2 and Fig.3 for all the recorded speech samples. Statistical significance test is performed on the collected data as explained in statistical analysis. Severity of cleft lip and palate speech is determined by comparing the frequencies of normal and abnormal subjects. B. Statistical Analysis Statistical significance plays a pivotal role in statistical hypothesis testing, where it is used to determine whether a null hypothesis should be rejected or retained. A null hypothesis is the general or default statement that nothing happened or changed. For a null hypothesis to be rejected as false, the result has to be identified as being statistically significant, i.e. unlikely to have occurred due to sampling error alone. Statistical significance (or a statistically significant result) is attained when a p-value is less than the significance level. The p-value is the probability of observing an effect given that the null hypothesis is true whereas the significance or alpha (α) level is the probability of rejecting the null hypothesis given that it is true. As a matter of good scientific practice, a significance level is chosen before data collection and is usually set to 0.05 (5%). To determine whether a result is statistically significant, a researcher would have to calculate a p-value. The null hypothesis is rejected if the p-value is less than the significance or α level. Then a statistically significant result is one in which the observed p-value is less than 5%, which is formally written as p < 0.05. Groups Mean Std.Deviation P- value 722.371 252.2081.264 534.214 341.5755 3427.000 1959.7777.125 5664.429 3003.1223 5160.286 2107.6548.047* 7908.571 2521.8159 590.171 311.6379.072 304.043 222.8886 4709.429 1713.8510.601 5402.143 2953.1293 6266.143 1975.0414.034* 8925.571 2176.7326 620.343 309.6256.218 400.286 323.2434 4530.143 2075.7853.300 6330.286 3877.8609 6336.857 2808.7712.080 10316.000 4733.6335 697.314 247.3509.200 503.071 287.4014 4675.714 1759.6692.898 4830.143 2584.2979 6079.000 2101.8577.115 7835.714 1755.8902 853.100 156.8849.072 561.000 359.1043 3973.714 1178.2840.128 6120.429 3270.4398 Normal 5143.429 1138.9641.006* 9117.571 2913.9233 All rights reserved by www.ijsrd.com 329

648.314 382.214 342.6600 197.2412 Ba F2 Normal 4873.571 1804.3308 7226.571 2719.5984 6463.429 1721.6239 9752.857 2728.3983 620.986 333.9783 579.057 239.4761 Ra F2 Normal 5138.571 2653.7504 7482.571 2750.6664 6137.286 2828.8324 9353.571 2211.4222 527.057 268.5898 632.643 179.2960 La F2 Normal 4839.329 2937.8389 5119.714 1870.3888 6367.286 2702.1646 7887.714 1102.7554 398.643 319.7461 511.786 343.0053 Na F2 Normal 3263.343 1753.3027 5273.429 3428.8081 4929.714 2508.2441 9677.000 4703.4159 Ma 426.514 363.4671 254.814 149.7106 F2 Normal 3380.186 1861.7825 6636.000 3459.0933 5071.429 2590.3742 9200.286 3147.1980 Table.1 Statistical significance test on formant frequencies Here * indicating the value which is less than 0.05(p<0.05).The results of the Table.1 indicate that changes in 3rd formant is more significant compared to the changes in 1st and 2nd formant in cleft lip and palate speech. Hence 3rd formant (F3) can be utilized to determine the severity of speech in cleft lip and palate. Syllable Formant frequency F3 Normal Difference Severity Ka 5160.286 7908.571 2748.285 Moderate Ga 6266.143 8925.571 2659.428 Moderate Cha 6336.857 10316.00 3979.143 Ja 6079.000 7835.714 1756.714 Mild Pa 5143.429 9117.571 3974.142 Ba 6463.429 9752.857 3289.428 Ra 6137.286 9353.571 3216.285 La 6367.286 7887.714 1520.428 Mild Na 4929.714 9677.000 4747.286 Severe Ma 5071.429 9200.286 4128.857 Severe Table 2: The values of F3 for normal and abnormal speech and their difference Table.2 shows the values of normal and abnormal speech and the difference between them. By observing the difference in the frequencies the severity of the speech is.100.081.019*.792.131.035*.404.835.193.535.192.036*.270.049*.020* classified as mild, moderate, moderately and with the guidance of speech pathologist. VI. CONCLUSION Cleft lip and cleft palate are usually caused by a combination of genes and other factors like what the mother eats or drinks or certain medications she uses during pregnancy. The cleft lip and palate in India is estimated approximately one in 781 births. It is also estimated that every year nearly 36,000 children with cleft palate are born in India. With proper diagnosis of children in the right time, speech disorder for the cleft lip and palate children can be reduced or completely nullify. The present study helps in determining speech disorders and it is also used in speech therapy to improve the speech intelligibility. The MATLAB software can be used to find out the severity of disordered speech and result can be concluded whether to undergo for a surgery or to give speech therapy for the children. REFERENCES [1] A. Barney, C.H. Shadle, and P.O.A.L. Davies, Fluid Flow in a Dynamical Mechanical Model of the Vocal Folds and Tract. 1: Measurements and Theory, J. Acoustical Society of America, vol. 105, no. 1, pp. 444 455, Jan. 1999. [2] Emmanual C. Ifeachor, Barrie W.Jervis, Digital Signal Processing A practical Approach, Person Education, Second Edition [3] American Cleft Palate-Craniofacial Association. 1993. Parameters for evaluation and treatment of patients with All rights reserved by www.ijsrd.com 330

cleft lip/palate or other craniofacial anomalies. Cleft Palate-Craniofacial Journal 30 (Suppl): S1-16. [4] Michael Peter Norton and Denis G. Karczub (2003). Fundamentals of Noise and Vibration Analysis for Engineers. Cambridge University Press. ISBN 0-521- 49913-5. [5] Craparo, Robert M. (2007). "Significance level". In Salkind, Neil J. Encyclopedia of Measurement and Statistics 3. Thousand Oaks, CA: SAGE Publications. pp. 889 891. ISBN 1-412-91611-9. [6] Healy, Joseph F. (2009). The Essentials of Statistics: A Tool for Social Research (2nd ed.). Belmont, CA: Cengage Learning. pp. 177 205. ISBN 0-495-60143-8. [7] Beriaghi S, Myers SL, Jensen SA, Kaimal S, Chan CM, Schaefer GB. Cleft lip and palate: association with other congenital malformations. J Clin Pediatr Dent. 2009;33:207 210. All rights reserved by www.ijsrd.com 331