• Journal of Audiology & Otology
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• v.25 no.1
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• pp.22-26
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• 2021

Background and Objectives: Music listening has a concomitant effect on structural and functional organization of the brain. It helps in relaxation, mind training and neural strengthening. In relation to it, the present study was aimed to find the effect of Carnatic music listening training (MLT) on speech in noise performance in adults. Subjects and Methods: A total of 28 participants (40-70 years) were recruited in the study. Based on randomized control trial, they were divided into intervention and control group. Intervention group underwent a short-term MLT. Quick Speech-in-Noise in Kannada was used as an outcome measure. Results: Results were analysed using mixed method analysis of variance (ANOVA) and repeated measures ANOVA. There was a significant difference between intervention and control group post MLT. The results of the second continuum revealed no statistically significant difference between post training and follow-up scores in both the groups. Conclusions: In conclusion short-term MLT resulted in betterment of speech in noise performance. MLT can be hence used as a viable tool in formal auditory training for better prognosis.

• Korean Journal of Audiology
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• v.25 no.1
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• pp.22-26
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• 2021

Background and Objectives: Music listening has a concomitant effect on structural and functional organization of the brain. It helps in relaxation, mind training and neural strengthening. In relation to it, the present study was aimed to find the effect of Carnatic music listening training (MLT) on speech in noise performance in adults. Subjects and Methods: A total of 28 participants (40-70 years) were recruited in the study. Based on randomized control trial, they were divided into intervention and control group. Intervention group underwent a short-term MLT. Quick Speech-in-Noise in Kannada was used as an outcome measure. Results: Results were analysed using mixed method analysis of variance (ANOVA) and repeated measures ANOVA. There was a significant difference between intervention and control group post MLT. The results of the second continuum revealed no statistically significant difference between post training and follow-up scores in both the groups. Conclusions: In conclusion short-term MLT resulted in betterment of speech in noise performance. MLT can be hence used as a viable tool in formal auditory training for better prognosis.

• Phonetics and Speech Sciences
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• v.14 no.2
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• pp.11-17
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• 2022

English vowels play an important role in verbal communication. However, Korean students tend to experience difficulty pronouncing a certain set of vowels despite extensive education in English. The aim of this study is to apply speech recognition software to evaluate Korean students' pronunciation of English vowels in minimal pair words and then to examine acoustic characteristics of the pairs in order to check their pronunciation problems. Thirty female Korean college students participated in the recording. Speech recognition rates were obtained to examine which English vowels were correctly pronounced. To compare and verify the recognition results, such acoustic analyses as the first and second formant trajectories and durations were also collected using Praat. The results showed an overall recognition rate of 54.7%. Some students incorrectly switched the tense and lax counterparts and produced the same vowel sounds for qualitatively different English vowels. From the acoustic analyses of the vowel formant trajectories, some of these vowel pairs were almost overlapped or exhibited slight acoustic differences at the majority of the measurement points. On the other hand, statistical analyses on the first formant trajectories of the three vowel pairs revealed significant differences throughout the measurement points, a finding that requires further investigation. Durational comparisons revealed a consistent pattern among the vowel pairs. The author concludes that speech recognition and analysis software can be useful to diagnose pronunciation problems of English-language learners.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.499-510
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• 2020

This study aims to analyze the causes of Internet hate speech, which has recently been emerging as a serious social problem and to seek for countermeasures. The experiences of hate speech are examined through the analysis of college students' essays and the causes and solutions of hate speech are suggested through the in-depth interviews with the experts. College students experience hate speech on the Internet on the basis of attributes such as age, gender, sexual orientation, and regionalism. Online comments on news, social media and online games are the main sources in spreading hate speech. On a personal level the lack of awareness of human dignity and the absence of media education are diagnosed as the reasons for online hate speech. The social reasons for online hate speech lie in the lack of human rights education and the problems of the media. In order to improve the problems of Internet hate speech, various suggestions are proposed on the legal, social and educational levels.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.1-10
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• 2023

This study investigated the relative effectiveness of letter-based versus syllable-based measures of speech rate and articulation rate in predicting the articulation score, prosody fluency, and rating sum using "English speech data of Koreans for education" from AI Hub. We extracted and analyzed 900 utterances from the training data, including three balanced age groups (13, 19, and 26 years old). The study built three models that best predicted the pronunciation assessment scores using linear mixed-effects regression and compared the predicted scores with the actual scores from the validation data (n=180). The correlation coefficients between them were also calculated. The findings revealed that syllable-based measures of speech and articulation rates were more effective than letter-based measures in all three pronunciation assessment categories. The correlation coefficients between the predicted and actual scores ranged from .65 to .68, indicating the models' good predictive power. However, it remains inconclusive whether speech rate or articulation rate is more effective.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.4
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• pp.494-506
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• 2012

The purpose of this study was to analyse 3, 4, 5-year-old children's private speech according to their age and task characteristics (structured task vs. unstructured task). In order to achieve the goal, the main effect of age, characteristic of tasks and interaction effect were considered among age and characteristic of tasks on preschool children's private speech. The subjects were each 30 3, 4, 5-year-olds from preschool in Busan, South Korea. The structured task was puzzle task and the unstructured task was drawing task from TCT-DP. The data was analyzed by repeated measurement two way ANOVA: 3(age) ${\times}$ 2((characteristic of task). As a result, firstly, total private speech of 4-year-old was higher than 3-year-old, 5-year-old in both tasks, and total private speech of 5-year-old was higher than 3-year-old in both tasks. Secondly, the task-irrelevant private speech was not affected by main effect of age and characteristic of task and interaction effect between age and characteristic of task. Thirdly, the task-relevant private speech was received both main effects and interaction effects between age and characteristic of task. Finally, the external manifestation of inner speech were not received effect of age but received effect of characteristic of task, and received interaction effect between age and characteristic of task. The results of this study imply that characteristic of task is an important factor inducing children's private speech.

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.43-50
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• 2017

These days voice models of speech recognition software are sophisticated enough to process the natural speech of people without any previous training. However, not much research has reported on the use of speech recognition tools in the field of pronunciation education. This paper examined Google speech recognition of a short English paragraph produced by Korean college students in clear and casual speech styles in order to diagnose and resolve students' pronunciation problems. Thirty three Korean college students participated in the recording of the English paragraph. The Google soundwriter was employed to collect data on the word recognition rates of the paragraph. Results showed that the total word recognition rate was 73% with a standard deviation of 11.5%. The word recognition rate of clear speech was around 77.3% while that of casual speech amounted to 68.7%. The reasons for the low recognition rate of casual speech were attributed to both individual pronunciation errors and the software itself as shown in its fricative recognition. Various distributions of unrecognized words were observed depending on each participant and proficiency groups. From the results, the author concludes that the speech recognition software is useful to diagnose each individual or group's pronunciation problems. Further studies on progressive improvements of learners' erroneous pronunciations would be desirable.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1135-1148
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• 2017

Speech recognition is one of the fascinating fields in the area of Computer science. Accuracy of speech recognition system may reduce due to the presence of noise present in speech signal. Therefore noise removal is an essential step in Automatic Speech Recognition (ASR) system and this paper proposes a new technique called combined thresholding for noise removal. Feature extraction is process of converting acoustic signal into most valuable set of parameters. This paper also concentrates on improving Mel Frequency Cepstral Coefficients (MFCC) features by introducing Discrete Wavelet Packet Transform (DWPT) in the place of Discrete Fourier Transformation (DFT) block to provide an efficient signal analysis. The feature vector is varied in size, for choosing the correct length of feature vector Self Organizing Map (SOM) is used. As a single classifier does not provide enough accuracy, so this research proposes an Ensemble Support Vector Machine (ESVM) classifier where the fixed length feature vector from SOM is given as input, termed as ESVM_SOM. The experimental results showed that the proposed methods provide better results than the existing methods.

• Speech Sciences
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• v.14 no.3
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• pp.147-160
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• 2007

This study was aimed to evaluate effect of parents-centered speech intervention program on overall speech and language performances of children with cochlear implant. Ten pairs of mother and child were selected and assigned into two groups: intervention group(G1) and control group(G2). G1 included 5 children with cochlear implant and their mothers who joined the parents-centered program. G2 consisted of 5 children with cochlear implant and their mothers did not participate in the program. To evaluate their speech and language abilities, examination instruments(Preschool Language Scale, and Language Comprehension and Cognition Test) were analyzed. Performances of pre- and post-treatment were analysed by ANOVA procedure. The results were as follows: There were significant differences of speech and language performances between pre- and post-treatment in G1. But there were no significant differences in G2(therapists centered program). G1 showed better performances in language comprehension than G2. This study revealed that parents centered language intervention program would be effective for speech and language development for children with cochlear implant.

• Phonetics and Speech Sciences
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• v.7 no.3
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• pp.153-163
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• 2015

This study investigated the trends of mobile applications which were developed for prompting speech and language skills for children with disabilities, and analyzed the function and contents of these applications as a tool of speech and language therapy. For this analysis, twenty applications among 71 ones were selected according to the exclusion criteria. These applications were classified by the 8 using types of contents and analyzed the function of mobile applications by the revised mobile contents evaluation standard (ease of use, value of education, interest level, and interactivity). As a results, applications for augmentative and alternative communication were developed much more than any other types. And the ease of use got the highest score whereas the interest level got the lowest score in whole evaluation analysis. The result of this study would suggest way to evaluate applications for speech language therapy and to contribute to developing the contents and function of mobile applications aims to help children with disabilities improving their speech and language skills.