• Phonetics and Speech Sciences
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• v.8 no.3
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• pp.1-9
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• 2016

This paper investigated the phoneme distribution and phonological processes of orthographic and pronounced phrasal words in light of syllable structure in the Seoul Corpus in order to provide linguists and phoneticians with a clearer understanding of the Korean language system. To achieve the goal, the phrasal words were extracted from the transcribed label scripts of the Seoul Corpus using Praat. Following this, the onsets, peaks, codas and syllable types of the phrasal words were analyzed using an R script. Results revealed that k0 was most frequently used as an onset in both orthographic and pronounced phrasal words. Also, aa was the most favored vowel in the Korean syllable peak with fewer phonological processes in its pronounced form. The total proportion of all diphthongs according to the frequency of the peaks in the orthographic phrasal words was 8.8%, which was almost double those found in the pronounced phrasal words. For the codas, nn accounted for 34.4% of the total pronounced phrasal words and was the varied form. From syllable type classification of the Corpus, CV appeared to be the most frequent type followed by CVC, V, and VC from the orthographic forms. Overall, the onsets were more prevalent in the pronunciation more than the codas. From the results, this paper concluded that an analysis of phoneme distribution and phonological processes in light of syllable structure can contribute greatly to the understanding of the phonology of spoken Korean.

• Phonetics and Speech Sciences
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• v.8 no.2
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• pp.11-16
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• 2016

This study explores the phoneme distribution and syllable structure of entry words in the CMU English Pronouncing Dictionary to provide phoneticians and linguists with fundamental phonetic data on English word components. Entry words in the dictionary file were syllabified using an R script and examined to obtain the following results: First, English words preferred consonants to vowels in their word components. In addition, monophthongs occurred much more frequently than diphthongs. When all consonants were categorized by manner and place, the distribution indicated the frequency order of stops, fricatives, and nasals according to manner and that of alveolars, bilabials and velars according to place. These results were comparable to the results obtained from the Buckeye Corpus (Yang, 2012). Second, from the analysis of syllable structure, two-syllable words were most favored, followed by three- and one-syllable words. Of the words in the dictionary, 92.7% consisted of one, two or three syllables. This result may be related to human memory or decoding time. Third, the English words tended to exhibit discord between onset and coda consonants and between adjacent vowels. Dissimilarity between the last onset and the first coda was found in 93.3% of the syllables, while 91.6% of the adjacent vowels were different. From the results above, the author concludes that an analysis of the phonetic symbols in a dictionary may lead to a deeper understanding of English word structures and components.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2002.05a
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• pp.111-116
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• 2002

The regularity effect for printed word recognition and naming depends on ambiguities between single letters (small grain-size) and their phonemic values. As a given word is repeated and becomes more familiar, letter-aggregate size (grain-size) is predicted to increase, thereby decreasing the ambiguity between spelling pattern and phonological representation and, therefore, decreasing the regularity effect. Lexical decision and naming tasks studied the effect of repetition on the regularity effect for words. The familiarity of a word from was manipulated by presenting low and high frequency words as well as by presenting half the stimuli in mixed upper- and lowercase letters (an unfamiliar form) and half in uniform case. In lexical decision, the regularity effect was initially strong for low frequency words but became null after two presentations; in naming it was also initially strong but was merely reduced (although still substantial) after three repetitions. Mixed case words were recognized and named more slowly and tended to show stronger regularity effects. The results were consistent with the primary hypothesis that familiar word forms are read faster because they are processed at a larger grain-size, which requires fewer operations to achieve lexical selection. Results are discussed in terms of a neurobiological model of word recognition based on brain imaging studies.

• Phonetics and Speech Sciences
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• v.10 no.2
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• pp.25-31
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• 2018

This paper investigated the phonological processes of monophthongs and diphthongs in the pronounced words present in the Buckeye Corpus and compared the frequency distribution of these processes by sex and age groups to provide a clearer understanding of spoken English to linguists and phoneticians. Both orthographic and pronounced words were extracted from the transcribed label scripts of the Buckeye Corpus using R. Next, the phonological processes of monophthongs and diphthongs in the orthographic and pronounced labels were tabulated using R scripts, and a frequency distribution by vowel process types, as well as sex and age groups, was created. The results revealed that 95% of the orthographic words contained the same number of syllables, whereas 5% had different numbers of vowels, thereby proving that speakers tend to preserve vowels in spontaneous speech. In addition, deletion processes were preferred in natural speech. Most vowel deletions occurred with an unstressed syllable. Chi-square tests were performed to calculate dependence in the distribution of phonological process types for male and female groups and young and old groups. The results showed a very strong correlation. This finding indicates that vowel processes occurred in approximately the same pattern in natural and spontaneous speech data regardless of sex and age, as well as whether or not the vowel processes were identical. Based on these results, the author concludes that an analysis of phonological processes in spontaneous speech corpora can greatly enhance practical understanding of spoken English.

• Journal of Korea Trade
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• v.24 no.5
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• pp.71-86
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• 2020

Purpose - This study investigates research trends by searching for English keywords and abstracts in 1,511 Korean journal articles in the Korea Citation Index from the 2002-2019 period using the term "Port." The study aims to lay the foundation for a more balanced development of port research. Design/methodology - Using abstract and keyword data, we perform frequency analysis and word embedding (Word2vec). A t-SNE plot shows the main keywords extracted using the TextRank algorithm. To analyze which words were used in what context in our two nine-year subperiods (2002-2010 and 2010-2019), we use Scattertext and scaled F-scores. Findings - First, during the 18-year study period, port research has developed through the convergence of diverse academic fields, covering 102 subject areas and 219 journals. Second, our frequency analysis of 4,431 keywords in 1,511 papers shows that the words "Port" (60 times), "Port Competitiveness" (33 times), and "Port Authority" (29 times), among others, are attractive to most researchers. Third, a word embedding analysis identifies the words highly correlated with the top eight keywords and visually shows four different subject clusters in a t-SNE plot. Fourth, we use Scattertext to compare words used in the two research sub-periods. Originality/value - This study is the first to apply abstract and keyword analysis and various text mining techniques to Korean journal articles in port research and thus has important implications. Further in-depth studies should collect a greater variety of textual data and analyze and compare port studies from different countries.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.510-515
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• 2001

Generally, there are (1)Words for conversation (2)Tone (3)Pitch (4)Formant frequency (5)Speech speed, etc as the element for emotional recognition from speech signal. For human being, it is natural that the tone, vice quality, speed words are easier elements rather than frequency to perceive other s feeling. Therefore, the former things are important elements fro classifying feelings. And, previous methods have mainly used the former thins but using formant is good for implementing as machine. Thus. our final goal of this research is to implement an emotional recognition system based on pitch, formant, speech speed, etc. from speech signal. In this paper, as first stage we foun specific features of feeling angry from his words when a man got angry.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.433-437
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• 2010

Patent contains meaningful technical achievement. There are many cases explaining technology trends from the analysis of frequency of term. Term sometimes has different meaning on fields. In this paper, words from patent titles of US, Japan, Korea PCT and EPO are collected by the 5 categories of WIPO. Frequency changes rate of each word were calculated and high ranked words of 5 categories were analyzed to find relationship between patent and technology development as well as technology trends.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.595-602
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• 2008

The focused word of each sentence is a help in recognizing and understanding spoken Korean. To find the method of focused word spotting at spoken speech signal, we made an analysis of the average and variance of Fundamental Frequency and the average energy extracted from a focused word and the other words in a sentence by experiments with the speech data from 100 spoken sentences. The result showed that focused words have either higher relative average F0 or higher relative variances of F0 than other words. Our findings are to make a contribution to getting prosodic characteristics of spoken Korean and keyword extraction based on natural language processing.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.2
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• pp.57-72
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• 2018

In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.839-846
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• 1995

In this paper, the spelling errors which are made by human being in the real word processors are collected and analyzed. Based on these data, we make a prototype which can perform spell aid function providing candidate words. The number of candidate characters are minimized by the frequency of Jaso and character, so the number of candidate words could be minimized. The average number of candidate words presented are 3.2 to 8, and 62.1 % to 84.1% of the correct words are presented in the candidate words.