• Phonetics and Speech Sciences
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• v.12 no.4
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• pp.91-98
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• 2020

This study investigated the acoustic characteristics of sustained vowel /a/ and sentence utterance produced by patients with muscle tension dysphonia (MTD) using cepstrum-based acoustic variables. 36 women diagnosed with MTD and the same number of women with normal voice participated in the study and the data were recorded and measured by ADSVTM. The results demonstrated that cepstral peak prominence (CPP) and CPP_F0 among all of the variables were statistically significantly lower than those of control group. When it comes to the GRBAS scale, overall severity (G) was most prominent, and roughness (R), breathiness (B), and strain (S) indices followed in order in the voice quality of MTD patients. As these characteristics increased, a statistically significant negative correlation was observed in CPP. We tried to classify MTD and control group using CPP and CPP_F0 variables. As a result of statistic modeling with a Random Forest machine learning algorithm, much higher classification accuracy (100% in training data and 83.3% in test data) was found in the sentence reading task, with CPP being proved to be playing a more crucial role in both vowel and sentence reading tasks.

• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.61-67
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• 1998

In this thesis, experiment have performed with the speaker recognition using multilayer feedforward neural network(MFNN) model using Korean and Japanese digits . The 5 adult males and 5 adult females pronounciate form 0 to 9 digits of Korean, Japanese 7 times. And then, they are extracted characteristics coefficient through Pitch deletion algorithm, LPC analysis, and LPC Cepstral analysis to generate input pattern of MFNN. 5 times among them are used to train a neural network, and 2 times is used to measure the performance of neural network. Both Korean and Japanese, Pitch coefficients is about 4%t more enhanced than LPC or LPC Cepstral coefficients.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.59-66
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• 2022

This research conducted a study classifying gender of speakers by analyzing feature vectors extracted from the voice data. The study provides convenience in automatically recognizing gender of customers without manual classification process when they request any service via voice such as phone call. Furthermore, it is significant that this study can analyze frequently requested services for each gender after gender classification using a learning model and offer customized recommendation services according to the analysis. Based on the voice data of males and females excluding blank spaces, the study extracts feature vectors from each data using MFCC(Mel Frequency Cepstral Coefficient) and utilizes SVM(Support Vector Machine) models to conduct machine learning. As a result of gender classification of voice data using a learning model, the gender recognition rate was 94%.

• Phonetics and Speech Sciences
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• v.11 no.1
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• pp.9-18
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• 2019

The purpose of this study is to determine whether the mean fundamental frequency (F0) changes depending on language, task, or language proficiency for Korean-English bilinguals. A total of forty-eight Korean-English speakers (28 balanced bilinguals and 20 Korean dominant bilinguals) participated in the study. Participants were asked to read aloud two types of tasks in English and Korean. For statistical analyses, the language ${\times}$ task two-way repeated ANOVAs were conducted within the balanced bilingual group first, and then group ${\times}$ language two-way mixed ANOVAs. The results showed that the females in both bilingual groups changed their mean F0 depending on the language they used and the tasks (p<.05), whereas no significant results were found in the males in either group under any conditions. The mean fundamental frequency in the Korean reading task was significantly higher than that in the English reading task for females in both balanced and Korean dominant bilingual groups. Thus, changes in mean F0 depending on language and context may reflect gender-specific characteristics, and females seem to be more sensitive to the socio-cultural standards that are imposed on them.

• Phonetics and Speech Sciences
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• v.11 no.2
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• pp.33-44
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• 2019

This paper dealt with how realization of pauses in utterance is affected by speech style, gender, and generation. For this purpose, we analyzed the frequency and duration of pauses. Pauses were categorized into four types: pause with breath, pause with no breath, utterance medial pause, and utterance final pause. Forty-eight subjects living in Seoul were chosen from the Korean Standard Speech Database. All subjects engaged in reading and spontaneous speech, through which we could also compare the realization between the two speech styles. The results showed that utterance final pauses had longer durations than utterance medial pauses. It means that utterance final pause has a function that signals the end of an utterance to the audience. For difference between tasks, spontaneous speech had longer and more frequent pauses because of cognitive reasons. With regard to gender variables, women produced shorter and less frequent pauses. For male speakers, the duration of pauses with breath was significantly longer. Finally, for generation variable, older speakers produced more frequent pauses. In addition, the results showed several interaction effects. Male speakers produced longer pauses, but this gender effect was more prominent at the utterance final position.

• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.17-25
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• 2023

This study examines the fundamental frequency(f0) distribution of 2,740 Korean speakers in a dialogue speech corpus. Praat and R were used for the collection and analysis of acoustical f0 data after removing extreme values considering the interquartile f0 range of the intonational phrases produced by each individual speaker. Results showed that the average f0 value of all speakers was 185 Hz and the median value was 187 Hz. The f0 data showed a positively skewed distribution of 0.11, and the kurtosis was -0.09, which is close to the normal distribution. The pitch values of daily conversations varied in the range of 238 Hz. Further examination of the male and female groups showed distinct median f0 values: 114 Hz for males and 199 Hz for females. A t-test between the two groups yielded a significant difference. The skewness representing the distribution shape was 1.24 for the male group and 0.58 for the female group. The kurtosis was 5.21 and 3.88 for the male and female groups, and the male group values appeared leptokurtic. A regression analysis between the median f0 and age yielded a slope of 0.15 for the male group and -0.586 for the female group, which indicated a divergent relationship. In conclusion, a normative f0 distribution of different Korean age and sex groups can be examined in the conversational speech corpus recorded by a massive number of participants. However, more rigorous data might be required to define a relation between age and f0 values.

• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.113-124
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• 2014

Ah! My Goddess has impressive narrative structure including a "narrative as a discourse," a "narrative as a story" and a "narrative by narrator": in a narrative as a discourse, North and South Korean soldiers make friendship; in a narrative by a narrator, main characters (including Sun-ho, Seok-gu, Ju-hwa, Chang-seop and Dong-hyeon) appear in the outer story and narrate the inner story of characters (including Dong-hyeon, Goddess and Seok-gu) within the frame of a play within a play; and in a narrative as a story, reality and fantasy intersect by the appearance of the "Goddess." This narrative structure contributes largely to 1) the character formation of space, 2) the strategic minimization of the stage, 3) the multiplicity of main characters, 4) the repetition of similar life story, and 5) the flexible change of a point of view. And the musical number serves as dramatic functions such as 1) pursuing the multiplicity of characters, 2) maximizing the effect of the expression of tragic feelings, 3) drawing audience's interest by irony and fantasy, 4) evoking the nostalgia for delicate feelings and pure wishes, and 5) ordinary female characters' playing the role of healing and salvation, thereby contributing to the reconstruction of reality and the style of fantasy.

• Phonetics and Speech Sciences
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• v.14 no.3
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• pp.41-49
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• 2022

The average acoustic distribution of American English speakers was statistically compared with the English-speaking patterns of gifted students in a Science Academy in Korea. By analyzing speech recordings, the duration time of which is much longer than in previous studies, this research identified the degree of acoustic proximity between the two parties and the predictability of English academic achievement of gifted high school students. Long-term spectral acoustic power distribution vectors were obtained for 2,048 center frequencies in the range of 20 Hz to 20,000 Hz by applying an long-term average speech spectrum (LTASS) MATLAB code. Three more variables were statistically compared to discover additional indices that can predict future English academic achievement: the receptive vocabulary size test, the cumulative vocabulary scores of English formative assessment, and the English Speaking Proficiency Test scores. Linear regression and correlational analyses between the four variables showed that the receptive vocabulary size test and the low-frequency vocabulary formative assessments which require both lexical and domain-specific science background knowledge are relatively more significant variables than a basic suprasegmental level English fluency in the predictability of gifted students' academic achievement.

• Phonetics and Speech Sciences
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• v.15 no.1
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• pp.9-17
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• 2023

The purpose of this study is to determine how the Korean diphthong /jo/ shows phonetic variation in various linguistic environments. The pronunciation of /jo/ is discussed, focusing on the relationship between phonetic variation and the distribution range of vowels. The location in a word (monosyllable, word-initial, word-medial, word-final) and word class (content word, function word) were analyzed using the speech of 10 female speakers of the Seoul Corpus. As a result of determining the frequency of appearance of /jo/ in each environment, the pronunciation type and word class were affected by the location in a word. Frequent phonetic reduction was observed in the function word /jo/ in the acoustic analysis. The word class did not change the average phonetic values of /jo/, but changed the distribution of individual tokens. These results indicate that the linguistic environment affects the phonetic distribution of vowels.

• Convergence Security Journal
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• v.23 no.1
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• pp.27-33
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• 2023

Digitalization due to COVID-19 has rapidly developed artificial intelligence-based voice recognition technology. However, this technology causes unfair social problems, such as race and gender discrimination if datasets are biased against some groups, and degrades the reliability and security of artificial intelligence services. In this work, we compare and analyze accuracy-based unfairness in biased data environments using VGGNet (Visual Geometry Group Network), ResNet (Residual Neural Network), and MobileNet, which are representative CNN (Convolutional Neural Network) models of artificial intelligence. Experimental results show that ResNet34 showed the highest accuracy for women and men at 91% and 89.9%in Top1-accuracy, while ResNet18 showed the slightest accuracy difference between genders at 1.8%. The difference in accuracy between genders by model causes differences in service quality and unfair results between men and women when using the service.