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Research on the changes in voice quality caused by tonsillectomy

Research on the changes in voice quality caused by tonsillectomy The article presents the results of the research on the changes in voice quality caused by tonsillectomy. It was carried out in a group of 20 patients (12 male and 8 female). The voice was recorded on a E-MU 0404 USB sound card with a 24-bit A/C AK5385A convertor. Having analyzed the pronunciation of prolonged Polish vowels: /a/, /e/, /i/ and /u/, the researchers defined a set of parameters which differentiate the pronunciation before and after tonsillectomy. The results show that the differences in pronunciation might be observed due to dynamic properties of the articulatory track. Additional researches emphasize the usefulness of such recordings applying external E-MU 0404 USB sound card in the clinical environment. KEYWORDS: tonsillectomy, surgical treatment, speech analysis, hypertrophy of tonsils Introduction Tonsillectomy always involves intervention within articulatory structures of the vocal track. As a result, many people are worried about possible changes in their voice. Therefore it is necessary to develop objective methods of evaluating voice changes resulting from tonsillectomy, which would make it possible to provide sufficient information for the patients, who are advised to undergo this form of treatment. In order to obtain a basis for reliable predictions, several patients had their voice signal recorded before and after tonsillectomy and a comparative analysis of voice signal parameters in both situations was carried out. The main objective of this paper is to present the set of differentiating parameters, which was defined during the research. Materials and methods The recordings were made at Otolaryngological Clinic of Collegium Medicum, Jagiellonian University in a special soundproof room designed for audiometric testing. Patients' speech was recorded twice. The first recording was made when the patients were still waiting for the surgery, 3 to 1 day before it, whereas the second one took place 6 weeks after the treatment at the same time as a medical checkout. 20 patients (12 male and 8 female) were examined this way after their tonsillectomy treatment. The research procedure consisted in recording the patients, who were reading a previously prepared text. The text was read three times. It included prolonged vowels: /a/, /e/, /i/ and /u/, which were focused on in further analysis. Patients' recordings, both preceding and following the tonsillectomy, were accompanied by a medical interview. Patients also had to fill in a questionnaire, in which they were asked to evaluate various aspects of their voice quality using a four-point scale. Collecting empirical material was followed by a parameter analysis. Before the analysis the voice signal was standardized so that its mean value approximated zero and its RMS value ranged between 0,16 and 0,17. As tonsillectomy involves the upper part of articulatory track, the voice changes were expected mainly in the parameters describing the frequency values of the vocal track. The set of parameters, which were analyzed during the research, included various amplitude values (A1, A2, A3, A4) and various frequencies of the first four formants (F1, F2, F3, F4). They were defined by means of LPC (Linear Prediction Code) analysis. The idea of LPC analysis is based on selecting the transmittance quotients , which modify the vocal track (1) so that the model error is as little as possible. The error is defined as an integral of a square of the difference between the model's reply and the actual signal route (2). (1) [ )] (2) - n-th sample of the observed signal - prediction order - the number of available samples during The model described above presents a formant nature of the vocal signal, as the transmittance (1) poles correspond to formant frequencies of the articulation track. The values which minimize (2) should be calculated by means of p set of equations: (3) where i = 1, 2 ... p. In order to solve the set of equations (3) Levinson-Durbin's algorithm was applied. Equations describing an iterative step of this algorithm are presented below [23]. The following symbols are introduced: - signal autocorrelation quotient - order prediction quotients - mean-square error Recursive relations might be presented by a formula (4). ] [ ] (4) [ where (5) assuming that and (6) (7) (6) and (7) lead to the conclusion that increasing the order prediction does not have a negative influence on its quality. Having defined prediction quotients, amplitude and formant frequency are defined on the basis of amplitude-frequency characteristics of the model (1) as shown in Figure 1. Figure 1. Amplitude-frequency characteristic of the female's voice track for vowel /a/. Next parameters, which are significant in the research are 20 successive mel-frequency cepstral coefficients for 300-mel wide filters (MC1,..., MC20). The idea of applying mel-scale cepstral parameters results from nonlinear frequency resolution of human ear. Frequency resolution of an organ of hearing means the minimal difference in frequency between two signals of the same amplitude, which a human is able to distinguish. Within the frequency up to 1 kHz constant resolution of the organ of hearing is assumed, however, for higher frequencies minimal differences of sine wave frequencies, which a human ear can differentiate is increasing. As a result, so-called mel scale was used, which reflected the subjective capability of frequency perception for a human ear. The reference point was specified as the signal of 1 kHz frequency and the amplitude 40 dB higher than the audibility threshold. The signal was assumed to correspond to the level of 1000 mels. In order to present the characteristics of human hearing on a frequency scale the following correlation was established (8) [11,13]. (8) Mel-cepstral analysis is based on the results of filtering the signal spectrum through the set of triangular filters with the same base width measured in the mel scale. Successive filters are half-width shifted in relation to each other so that the sum of their characteristics' values was equal 1, within the range of sound frequency of human speech (Figure 2). Figure 2. Relation between frequency in Hz and in mel-scale. When the signal has been filtered by all the filters from the set, the integral of the results is calculated. The complex vector which is obtained from the integration results must undergo cepstral analysis. The result of this process is the set of mel-cepstral quotients, the number of which corresponds to the number of filters. [ ( )] (9) where: ­ n-th cepstral quotient, ­ i-th quotient obtained as a result of integration of the spectrum filtered by the i-th filter from the set (Figure 3), Z ­ the number of filters. Figure 3. Combination of characteristics of triangular mel-filters used to compute mel-frequency cepstral coefficients. The object of the research was also the signal energy emission in the frequency ranges corresponding to successive formants. The results were described by means of power factors defined by the formula (10) (W1, W2, W3, W4). The power factor formula within the range of the n-th formant is presented below: | | | | (10) represents the power factor of a signal related to frequency. and are the frequencies which describe the limits within which the successive formants of particular vowels appear. Frequency limits based on the research [11] was used. They were specified after the analysis of the speech of a group of patients who did not complain about any vocal disorders. In order to present the energy share of a higher frequency signal in the speech signal spectrum standardized spectral moments of the first, second and third level were additionally used (M1, M2, M3). Spectral moments are used to evaluate the energy share of higher frequency components in the overall signal emission. They are generally described by means of the formula (11): | | [ ] (11) where: - power factor value of the l-th range of analyzed frequencies, - mean frequency of the l-th range The sum which is used in formula (11) is, in practice, limited to the number of frequency ranges which are analyzed. Spectrum order (m) is responsible for the sensitivity of the spectrum moment to a change in signal energy in the higher frequency ranges. The higher the order, the higher sensitivity to these changes. Recordings with various signal energy need to be standardized before comparative analysis. Spectrum moments of the m-th level are standardized in relation to the zero order moment by the following formula (12): (12) While selecting the parameters which allow for proper evaluation of tonsillectomy-triggered voice changes, it should be noted that some changes might have resulted from the disorders because of which the patient had to undergo the surgery. It might have been, for example, inflammation or partial paralysis of some speech organ. The most significant influence upon the speech signal have the disorders involving vocal folds and their functions. Therefore the set of analyzed parameters has been completed with the factors which define the speech irregularity level such as Jitter, Shimmer, Power Perturbation Quotient (PPQ), Energy Perturbation Quotient (EPQ) and also standard deviation from the base frequency. PQ (Perturbation Quotient) is used to describe the changeability of the successive elements of the vector. It is calculated by means of formula (13) [10]: where refers to: successive values of base frequency for Jitter parameter, values of signal amplitude in successive base periods for Shimmer parameter, signal power value in successive base periods for PPQ, signal energy value in successive base periods for EPQ. refers to the number of available values of . (13) Selected set of parameters is characterized by a low changeability as far as a particular person is concerned and high changeability in relation to a group of people, which is vital for evaluating the influence of tonsillectomy on changes in voice parameters [11]. In order to define essential differences in the parameter values of statistical analysis t-Student test and F Snedecor's test have been used. The set of parameters differentiating the speech between and after the surgery was selected according to the following criteria: - T-Student's or F Snedecor's statistic value exceeds the critical value for the significance level of 0,95. - The distribution of value parameters for comparable groups is close to the normal one. This requirement is met when the skew and kurtosis fit into the confidence interval (-1,92; 1,92). This criterion allows to exclude from the set of parameters those, which are likely to bring false results, because of high risk of mistakes. - Variation values within comparable groups are not significantly different. It is assumed that a significant difference of variation values means that the proportion between the higher and lower value exceeds 2. This criterion verifies, to some extent, whether the groups examined might be considered representative for the whole population. The increase in the number of people examined might improve the variation value because for a given parameter the difference between variations in groups before and after the surgery is decreased. Therefore this indicator cannot firmly exclude the parameter from a differentiating set. Results Statistical analysis of calculated parameters of vowel pronunciation defined a set of acoustic parameters which differentiate the speech of the patients before and after the surgery in a significant way. The parameters differ depending on the vowels and the patient's sex. The set of features, which differentiate the speech of people before and after tonsillectomy is presented below. Female patients: - vowel /a/: F4, M2 - vowel /e/: MC20 - vowel /i/: MC10, MC16 - vowel /u/: MC3, MC10 Male patients: - vowel /a/: MC4, - vowel /e/: A1,A2 - vowel /i/: MC20, W1 - vowel /u/: MC5, MC12, MC14, MC15, MC19, W1 Table 1 and 2 contains mean values of parameters from the set differentiating the speech before and after the surgery. Standardized mean values of this parameters are also presented in the form of bar charts (Figure 4 and Figure 5). The results in Figure 4 and Figure 5 have been standardized so that the parameters with higher absolute value have a unit absolute value on the chart. Additionally, in order to illustrate the differences in exemplary parameters' values and also the direction of changes caused by tonsillectomy within the parameters presented, selected pairs of parameters, which differentiate the speech before and after surgery are presented in 2 D scale on Figure 6a and Figure 6b. Additionally, below there are listed parameters, for which a significant difference in the variation values for comparable groups has been observed, which means that statistical requirements haven't been met. It doesn't exclude them, however, from the set of differentiating parameters: Female patients: - vowel /a/: MC11 - vowel /u/: MC7 Male patients: - vowel /a/: W2 - vowel /e/: MC1, W4 1 0,5 0 -0,5 -1 before the surgery after the surgery Figure 4. The list of standardized values of average parameters from the set differentiating female speech before and after the surgery. 1 0,5 0 -0,5 -1 before the surgery after the surgery Figure 5. The list of standardized values of average parameters from the set differentiating male speech before and after the surgery. Figure 6a. 2D scale compilations of selected pairs of parameters differentiating the speech before and after tonsillectomy for female voice. Figure 6b. 2D scale compilations of selected pairs of parameters differentiating the speech before and after tonsillectomy for male voice. Table 1. Mean values of parameters from the set differentiating male speech before and after the surgery Parameter /a/-MC4 /e/-A1 /e/-A2 /i/-MC20 /i/-W1 /u/-MC5 /u/-MC12 /u/-MC14 /u/-MC15 /u/-MC19 /u/-W1 Value before the surgery -0,73 25,08 26,33 -0,43 0,22 -0,39 -0,8 -0,04 0,39 -0,75 0,19 Value after the surgery -1,65 20,33 21,33 -0,15 0,14 0,45 -1,44 0,43 -0,37 -0,21 0,27 Table 2. Mean values of parameters from the set differentiating female speech before and after the surgery Parameter /a/-F4 /a/-M2 /e/-MC20 /i/-MC10 /i/-MC16 /u/-MC3 /u/-MC10 Discussion Value before the surgery 4702,75 8815690 -0,32 -2,03 -0,41 6,62 -1,31 Value after the surgery 5182 11282511 0,04 -2,77 -0,89 4,73 -2,32 The analysis of the research results may lead to the conclusion that the voice samples recorded by means of a computer and an external sound card (especially E-MU 0404 USB sound card) in a soundproof hospital room are as much useful for the analysis of voice changes as the recordings made in a reverberation-free chamber. The results of statistical analysis of the defined parameters indicate that the voice changes following tonsillectomy are mainly connected with the value changes of the parameters measured by means of Fourier's spectrum of speech signal. They are caused by changes in the shape of the articulatory track. The results of the research analysis confirm the results of researches carried out by other authors. It refers particularly to the increasing F4 frequency for /a/ vowel pronounced by women. The next conclusion drawn from the research is a very high number of mel-cepstral parameters among the parameters differentiating the patients' speech before and after tonsillectomy. This fact accounts for a high usefulness of this type of analysis in evaluating voice changes resulting from the medical invasion in the articulatory track. The results indicated also changes of F1 and F2 amplitude value for /e/ vowel pronounced by men and the changes connected with the energy emission within the frequency of the first formant of /i/ and /u/ vowels pronounced by men too. It was also discovered that the A1 and A2 values of /e/ vowel and W1 value of /i/ vowel are statistically lower after the surgery, whereas the W1 value of /u/ vowel is higher. These results indicate significant changes in the spectrum structure of the speech signal for the male part of the population undergoing tonsillectomy. To sum up, the results of the research carried out for this thesis do not question the results obtained by other researchers, and, in some cases, they confirm the data presented in other publications on the voice changes following tonsillectomy. The most valuable conclusion is that mel-cepstral parameters play an important role in differentiating the sounds before and after the surgery. It seems essential, however, to continue the research in order to verify the usefulness of specific mel-cepstral parameters in differentiating the speech changes in a bigger group of patients. Further research is also necessary to verify the changes observed around the first and the second formant frequency of male speech, because such changes have never been described before in widely known publications, even though the publications mention the research on the formant structure of speech. It might be explained either as a coincidence accompanying the research or as a discovery of an absolutely new phenomenon. Conclusions The research results imply that it is possible to apply a much wider set of parameters which differentiate the speech before and after tonsillectomy than it was suggested in the previous publications. Mel-cepstral parameters have been proved to be particularly useful in differentiating the speech before and after the surgery. It should be noted, however, that the results must be verified in a bigger group of respondents. The usefulness of recordings produced on an external sound card and the PC computer should also be emphasized. It implies a possibility of a wider application of this measurement method for speech pathologies, which means that the availability of this form of diagnostics should be increased. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bio-Algorithms and Med-Systems de Gruyter

Research on the changes in voice quality caused by tonsillectomy

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de Gruyter
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Copyright © 2012 by the
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1895-9091
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1896-530X
DOI
10.2478/bams-2012-0010
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Abstract

The article presents the results of the research on the changes in voice quality caused by tonsillectomy. It was carried out in a group of 20 patients (12 male and 8 female). The voice was recorded on a E-MU 0404 USB sound card with a 24-bit A/C AK5385A convertor. Having analyzed the pronunciation of prolonged Polish vowels: /a/, /e/, /i/ and /u/, the researchers defined a set of parameters which differentiate the pronunciation before and after tonsillectomy. The results show that the differences in pronunciation might be observed due to dynamic properties of the articulatory track. Additional researches emphasize the usefulness of such recordings applying external E-MU 0404 USB sound card in the clinical environment. KEYWORDS: tonsillectomy, surgical treatment, speech analysis, hypertrophy of tonsils Introduction Tonsillectomy always involves intervention within articulatory structures of the vocal track. As a result, many people are worried about possible changes in their voice. Therefore it is necessary to develop objective methods of evaluating voice changes resulting from tonsillectomy, which would make it possible to provide sufficient information for the patients, who are advised to undergo this form of treatment. In order to obtain a basis for reliable predictions, several patients had their voice signal recorded before and after tonsillectomy and a comparative analysis of voice signal parameters in both situations was carried out. The main objective of this paper is to present the set of differentiating parameters, which was defined during the research. Materials and methods The recordings were made at Otolaryngological Clinic of Collegium Medicum, Jagiellonian University in a special soundproof room designed for audiometric testing. Patients' speech was recorded twice. The first recording was made when the patients were still waiting for the surgery, 3 to 1 day before it, whereas the second one took place 6 weeks after the treatment at the same time as a medical checkout. 20 patients (12 male and 8 female) were examined this way after their tonsillectomy treatment. The research procedure consisted in recording the patients, who were reading a previously prepared text. The text was read three times. It included prolonged vowels: /a/, /e/, /i/ and /u/, which were focused on in further analysis. Patients' recordings, both preceding and following the tonsillectomy, were accompanied by a medical interview. Patients also had to fill in a questionnaire, in which they were asked to evaluate various aspects of their voice quality using a four-point scale. Collecting empirical material was followed by a parameter analysis. Before the analysis the voice signal was standardized so that its mean value approximated zero and its RMS value ranged between 0,16 and 0,17. As tonsillectomy involves the upper part of articulatory track, the voice changes were expected mainly in the parameters describing the frequency values of the vocal track. The set of parameters, which were analyzed during the research, included various amplitude values (A1, A2, A3, A4) and various frequencies of the first four formants (F1, F2, F3, F4). They were defined by means of LPC (Linear Prediction Code) analysis. The idea of LPC analysis is based on selecting the transmittance quotients , which modify the vocal track (1) so that the model error is as little as possible. The error is defined as an integral of a square of the difference between the model's reply and the actual signal route (2). (1) [ )] (2) - n-th sample of the observed signal - prediction order - the number of available samples during The model described above presents a formant nature of the vocal signal, as the transmittance (1) poles correspond to formant frequencies of the articulation track. The values which minimize (2) should be calculated by means of p set of equations: (3) where i = 1, 2 ... p. In order to solve the set of equations (3) Levinson-Durbin's algorithm was applied. Equations describing an iterative step of this algorithm are presented below [23]. The following symbols are introduced: - signal autocorrelation quotient - order prediction quotients - mean-square error Recursive relations might be presented by a formula (4). ] [ ] (4) [ where (5) assuming that and (6) (7) (6) and (7) lead to the conclusion that increasing the order prediction does not have a negative influence on its quality. Having defined prediction quotients, amplitude and formant frequency are defined on the basis of amplitude-frequency characteristics of the model (1) as shown in Figure 1. Figure 1. Amplitude-frequency characteristic of the female's voice track for vowel /a/. Next parameters, which are significant in the research are 20 successive mel-frequency cepstral coefficients for 300-mel wide filters (MC1,..., MC20). The idea of applying mel-scale cepstral parameters results from nonlinear frequency resolution of human ear. Frequency resolution of an organ of hearing means the minimal difference in frequency between two signals of the same amplitude, which a human is able to distinguish. Within the frequency up to 1 kHz constant resolution of the organ of hearing is assumed, however, for higher frequencies minimal differences of sine wave frequencies, which a human ear can differentiate is increasing. As a result, so-called mel scale was used, which reflected the subjective capability of frequency perception for a human ear. The reference point was specified as the signal of 1 kHz frequency and the amplitude 40 dB higher than the audibility threshold. The signal was assumed to correspond to the level of 1000 mels. In order to present the characteristics of human hearing on a frequency scale the following correlation was established (8) [11,13]. (8) Mel-cepstral analysis is based on the results of filtering the signal spectrum through the set of triangular filters with the same base width measured in the mel scale. Successive filters are half-width shifted in relation to each other so that the sum of their characteristics' values was equal 1, within the range of sound frequency of human speech (Figure 2). Figure 2. Relation between frequency in Hz and in mel-scale. When the signal has been filtered by all the filters from the set, the integral of the results is calculated. The complex vector which is obtained from the integration results must undergo cepstral analysis. The result of this process is the set of mel-cepstral quotients, the number of which corresponds to the number of filters. [ ( )] (9) where: ­ n-th cepstral quotient, ­ i-th quotient obtained as a result of integration of the spectrum filtered by the i-th filter from the set (Figure 3), Z ­ the number of filters. Figure 3. Combination of characteristics of triangular mel-filters used to compute mel-frequency cepstral coefficients. The object of the research was also the signal energy emission in the frequency ranges corresponding to successive formants. The results were described by means of power factors defined by the formula (10) (W1, W2, W3, W4). The power factor formula within the range of the n-th formant is presented below: | | | | (10) represents the power factor of a signal related to frequency. and are the frequencies which describe the limits within which the successive formants of particular vowels appear. Frequency limits based on the research [11] was used. They were specified after the analysis of the speech of a group of patients who did not complain about any vocal disorders. In order to present the energy share of a higher frequency signal in the speech signal spectrum standardized spectral moments of the first, second and third level were additionally used (M1, M2, M3). Spectral moments are used to evaluate the energy share of higher frequency components in the overall signal emission. They are generally described by means of the formula (11): | | [ ] (11) where: - power factor value of the l-th range of analyzed frequencies, - mean frequency of the l-th range The sum which is used in formula (11) is, in practice, limited to the number of frequency ranges which are analyzed. Spectrum order (m) is responsible for the sensitivity of the spectrum moment to a change in signal energy in the higher frequency ranges. The higher the order, the higher sensitivity to these changes. Recordings with various signal energy need to be standardized before comparative analysis. Spectrum moments of the m-th level are standardized in relation to the zero order moment by the following formula (12): (12) While selecting the parameters which allow for proper evaluation of tonsillectomy-triggered voice changes, it should be noted that some changes might have resulted from the disorders because of which the patient had to undergo the surgery. It might have been, for example, inflammation or partial paralysis of some speech organ. The most significant influence upon the speech signal have the disorders involving vocal folds and their functions. Therefore the set of analyzed parameters has been completed with the factors which define the speech irregularity level such as Jitter, Shimmer, Power Perturbation Quotient (PPQ), Energy Perturbation Quotient (EPQ) and also standard deviation from the base frequency. PQ (Perturbation Quotient) is used to describe the changeability of the successive elements of the vector. It is calculated by means of formula (13) [10]: where refers to: successive values of base frequency for Jitter parameter, values of signal amplitude in successive base periods for Shimmer parameter, signal power value in successive base periods for PPQ, signal energy value in successive base periods for EPQ. refers to the number of available values of . (13) Selected set of parameters is characterized by a low changeability as far as a particular person is concerned and high changeability in relation to a group of people, which is vital for evaluating the influence of tonsillectomy on changes in voice parameters [11]. In order to define essential differences in the parameter values of statistical analysis t-Student test and F Snedecor's test have been used. The set of parameters differentiating the speech between and after the surgery was selected according to the following criteria: - T-Student's or F Snedecor's statistic value exceeds the critical value for the significance level of 0,95. - The distribution of value parameters for comparable groups is close to the normal one. This requirement is met when the skew and kurtosis fit into the confidence interval (-1,92; 1,92). This criterion allows to exclude from the set of parameters those, which are likely to bring false results, because of high risk of mistakes. - Variation values within comparable groups are not significantly different. It is assumed that a significant difference of variation values means that the proportion between the higher and lower value exceeds 2. This criterion verifies, to some extent, whether the groups examined might be considered representative for the whole population. The increase in the number of people examined might improve the variation value because for a given parameter the difference between variations in groups before and after the surgery is decreased. Therefore this indicator cannot firmly exclude the parameter from a differentiating set. Results Statistical analysis of calculated parameters of vowel pronunciation defined a set of acoustic parameters which differentiate the speech of the patients before and after the surgery in a significant way. The parameters differ depending on the vowels and the patient's sex. The set of features, which differentiate the speech of people before and after tonsillectomy is presented below. Female patients: - vowel /a/: F4, M2 - vowel /e/: MC20 - vowel /i/: MC10, MC16 - vowel /u/: MC3, MC10 Male patients: - vowel /a/: MC4, - vowel /e/: A1,A2 - vowel /i/: MC20, W1 - vowel /u/: MC5, MC12, MC14, MC15, MC19, W1 Table 1 and 2 contains mean values of parameters from the set differentiating the speech before and after the surgery. Standardized mean values of this parameters are also presented in the form of bar charts (Figure 4 and Figure 5). The results in Figure 4 and Figure 5 have been standardized so that the parameters with higher absolute value have a unit absolute value on the chart. Additionally, in order to illustrate the differences in exemplary parameters' values and also the direction of changes caused by tonsillectomy within the parameters presented, selected pairs of parameters, which differentiate the speech before and after surgery are presented in 2 D scale on Figure 6a and Figure 6b. Additionally, below there are listed parameters, for which a significant difference in the variation values for comparable groups has been observed, which means that statistical requirements haven't been met. It doesn't exclude them, however, from the set of differentiating parameters: Female patients: - vowel /a/: MC11 - vowel /u/: MC7 Male patients: - vowel /a/: W2 - vowel /e/: MC1, W4 1 0,5 0 -0,5 -1 before the surgery after the surgery Figure 4. The list of standardized values of average parameters from the set differentiating female speech before and after the surgery. 1 0,5 0 -0,5 -1 before the surgery after the surgery Figure 5. The list of standardized values of average parameters from the set differentiating male speech before and after the surgery. Figure 6a. 2D scale compilations of selected pairs of parameters differentiating the speech before and after tonsillectomy for female voice. Figure 6b. 2D scale compilations of selected pairs of parameters differentiating the speech before and after tonsillectomy for male voice. Table 1. Mean values of parameters from the set differentiating male speech before and after the surgery Parameter /a/-MC4 /e/-A1 /e/-A2 /i/-MC20 /i/-W1 /u/-MC5 /u/-MC12 /u/-MC14 /u/-MC15 /u/-MC19 /u/-W1 Value before the surgery -0,73 25,08 26,33 -0,43 0,22 -0,39 -0,8 -0,04 0,39 -0,75 0,19 Value after the surgery -1,65 20,33 21,33 -0,15 0,14 0,45 -1,44 0,43 -0,37 -0,21 0,27 Table 2. Mean values of parameters from the set differentiating female speech before and after the surgery Parameter /a/-F4 /a/-M2 /e/-MC20 /i/-MC10 /i/-MC16 /u/-MC3 /u/-MC10 Discussion Value before the surgery 4702,75 8815690 -0,32 -2,03 -0,41 6,62 -1,31 Value after the surgery 5182 11282511 0,04 -2,77 -0,89 4,73 -2,32 The analysis of the research results may lead to the conclusion that the voice samples recorded by means of a computer and an external sound card (especially E-MU 0404 USB sound card) in a soundproof hospital room are as much useful for the analysis of voice changes as the recordings made in a reverberation-free chamber. The results of statistical analysis of the defined parameters indicate that the voice changes following tonsillectomy are mainly connected with the value changes of the parameters measured by means of Fourier's spectrum of speech signal. They are caused by changes in the shape of the articulatory track. The results of the research analysis confirm the results of researches carried out by other authors. It refers particularly to the increasing F4 frequency for /a/ vowel pronounced by women. The next conclusion drawn from the research is a very high number of mel-cepstral parameters among the parameters differentiating the patients' speech before and after tonsillectomy. This fact accounts for a high usefulness of this type of analysis in evaluating voice changes resulting from the medical invasion in the articulatory track. The results indicated also changes of F1 and F2 amplitude value for /e/ vowel pronounced by men and the changes connected with the energy emission within the frequency of the first formant of /i/ and /u/ vowels pronounced by men too. It was also discovered that the A1 and A2 values of /e/ vowel and W1 value of /i/ vowel are statistically lower after the surgery, whereas the W1 value of /u/ vowel is higher. These results indicate significant changes in the spectrum structure of the speech signal for the male part of the population undergoing tonsillectomy. To sum up, the results of the research carried out for this thesis do not question the results obtained by other researchers, and, in some cases, they confirm the data presented in other publications on the voice changes following tonsillectomy. The most valuable conclusion is that mel-cepstral parameters play an important role in differentiating the sounds before and after the surgery. It seems essential, however, to continue the research in order to verify the usefulness of specific mel-cepstral parameters in differentiating the speech changes in a bigger group of patients. Further research is also necessary to verify the changes observed around the first and the second formant frequency of male speech, because such changes have never been described before in widely known publications, even though the publications mention the research on the formant structure of speech. It might be explained either as a coincidence accompanying the research or as a discovery of an absolutely new phenomenon. Conclusions The research results imply that it is possible to apply a much wider set of parameters which differentiate the speech before and after tonsillectomy than it was suggested in the previous publications. Mel-cepstral parameters have been proved to be particularly useful in differentiating the speech before and after the surgery. It should be noted, however, that the results must be verified in a bigger group of respondents. The usefulness of recordings produced on an external sound card and the PC computer should also be emphasized. It implies a possibility of a wider application of this measurement method for speech pathologies, which means that the availability of this form of diagnostics should be increased.

Journal

Bio-Algorithms and Med-Systemsde Gruyter

Published: Jan 1, 2012

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