This paper aims to reexamine the issue of racism in Conrad's Heart of Darkness, especially in the light of Chinua Achebe's critique of the novella as a racist text entrenched with European prejudices of Africa and its people in his 1975 speech at the University of Massachusetts titled "An Image of Africa." While the novella's indictment of imperial exploitation has been noted from an early stage of its critical reception, its racism had hardly been discussed until Chinua Achebe posed it. Achebe offers the canonized status of the text as a modernist classic, "the most commonly prescribed novel in twentieth-century literature courses," as one reason for its obvious manifestations of racism being glossed over. One may add that Conrad's militant denunciation of imperialist enterprises as "a sordid farce," his seemingly radical stance against imperialism, serves as ideological constraints upon his readers, blinding them to its immanent racism. A closer look at the novella's attack on imperialism turns out to be contradictory, for it also shows such liberal-humanist ideas as the civilizing mission, the work ethic, and the superiority of civilized man, all of which served to prop up European imperialism at the end of the nineteenth century. This ideological contradiction also accounts for Conrad's racist attitude, which is betrayed in his portrayal of Africans as obscure, primitive. Euro-American imperialism has frequently justified itself by recourse to racism, but racism has not always been allied with imperialism. Some staunch racists such as Robert Knox and Arthur de Gobineau went against imperialism, and Conrad proves one of such cases whose critique of imperialism is voiced in ways that can be characterized as racist.
In this paper, a contort- and speaker-dependent cepstrum extraction method and a channel normalization method for minimizing the loss of speaker characteristics in the cepstrum were proposed for a robust speaker recognition system over the channel. The proposed extraction method creates a cepstrum based on the pitch synchronous analysis using the inherent pitch of the speaker. Therefore, the cepstrum called the 〃pitch synchronous cepstrum〃 (PSC) represents the impulse response of the vocal tract more accurately in voiced speech. And the PSC can compensate for channel distortion because the pitch is more robust in a channel environment than the spectrum of speech. And the proposed channel normalization method, the 〃formant-broadened pitch synchronous CMS〃 (FBPSCMS), applies the Formant-Broadened CMS to the PSC and improves the accuracy of the intraframe processing. We compared the text-independent closed-set speaker identification on 56 females and 112 males using TIMIT and NTIMIT database, respectively. The results show that pitch synchronous km improves the error reduction rate by up to 7.7% in comparison with conventional short-time cepstrum and the error rates of the FBPSCMS are more stable and lower than those of pole-filtered CMS.
Kim, Tae-Guon;Kim, Bong-Wan;Choi, Dae-Lim;Lee, Yong-Ju
The Journal of the Korea Contents Association
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v.12
no.1
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pp.9-16
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2012
Though Android-based smart phones are being released in Korea, Korean TTS engine is not built on them and Google has not announced service or software developer's kit related to Korean TTS officially. Thus, application developers who want to include Korean TTS capability in their application have difficulties. In this paper, we design and implement Android OS-based Korean TTS system and service. For speed, text preprocessing and synthesis libraries are implemented using Android NDK. By using Java's thread mechanism and the AudioTrack class, the response time of TTS is minimized. For the test of implemented service, an application that reads incoming SMS is developed. The test shows that synthesized speech are generated in real-time for random sentences. By using the implemented Korean TTS service, Android application developers can transmit information easily through voice. Korean TTS service proposed and implemented in this paper overcomes shortcomings of the existing restrictive synthesis methods and provides the benefit for application developers and users.
The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.
Objectives: The aim of this study was to investigate the effects of handwriting on the writing assessment, according to whether the handwriting is excellent or bad. Methods: A total of 24 elementary and middle school teachers participated in this study and assessed 6 original writings and 6 transcriptions of the same original writings using the HWP 2007 program. Six writings were collected from elementary students of 4th to 6th grades, 3 of 6 students presented with excellent handwriting and 3 of 6 with bad handwriting. The assessments were done according to the standards of propositional knowledge assessment (You & Jeong, 2008). Results: In the excellent handwritings, the rules of orthography and the contents of introduction of the original writings were scored higher than those in the transcriptions. The difference between transcription and original writing showed minus scores in original writing assessments and plus scores in transcription assessments. In the propositional knowledge score and its subscales scores - content knowledge, text knowledge, language knowledge and text context knowledge -, were differences in transcription assessments significantly higher than those in original writing assessments. Several assessment indices - clarity of the ending, contents of introduction, appropriate contents, rules of orthography, structured composition and various vocabularies showed significantly higher differences in transcription assessments than those in original writing assessments. Conclusions: The excellent handwriting could be assessed high and the bad handwriting could be assessed low. These results suggest that we should consider the effects of handwriting factors on the results of writing assessment and that the transcription could be used for an accurate writing assessment.
Park, Soonwook;Jun, Hyeyoon;Kim, Yoonsoo;Lee, Soowon
Journal of the Korea Society of Computer and Information
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v.26
no.12
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pp.1-9
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2021
Disaster alerts are text messages sent by government to people in the area in the event of a disaster. Since the number of disaster alerts has increased, the number of people who block disaster alerts is increasing as many unnecessary disaster alerts are being received. To solve this problem, this study proposes a deep learning model that automatically classifies disaster alerts by disaster type, and allows only necessary disaster alerts to be received according to the recipient. The proposed model embeds disaster alerts via KoBERT and classifies them by disaster type with LSTM. As a result of classifying disaster alerts using 3 combinations of parts of speech: [Noun], [Noun + Adjective + Verb] and [All parts], and 4 classification models: Proposed model, Keyword classification, Word2Vec + 1D-CNN and KoBERT + FFNN, the proposed model achieved the highest performance with 0.988954 accuracy.
In this study, we examined the interactive aspects between pitch reduction phenomena considered a universal language phenomenon and native language interference in the production of L2 intonation performed by Chinese learners of Korean. To investigate their interaction, we conducted an acoustic analysis using acoustic measures such as pitch span, pitch level, pitch dynamic quotient, skewness, and kurtosis. In addition, the correlation between text comprehension and pitch was examined. The analyzed material consisted of four Korean discourses containing five and seven sentences of varying difficulty. Seven Korean native speakers and thirty Chinese learners who differed in their Korean proficiency participated in the production test. The results, for differences by language, showed that Chinese had a more expanded pitch span, and a higher pitch level than Korean. The analysis between groups showed that at the beginner and intermediate levels, pitch reduction was prominent, i.e., their Korean was characterized by a compressed pitch span, low pitch level, and less sentence internal pitch variation. Contrariwise, the pitch use of advanced speakers was most similar to Korean native speakers. There was no significant correlation between text difficulty and pitch use. Through this study, we observed that pitch reduction was more pronounced than native language interference in the phonetic layer.
Our research task have goal to describe a treaty rhetoric known as 『La Rhétorique ou L'Art de Parler』(1688) which corresponds to a very wide field of which the step is not yet dubious in our country. Thus to study the rhetoric of Lamy borrowed from the thought of Descartes, we left the concept d' origin of language in traditional rhetoric in connection with logic and grammar (in first part). Also the second part is devoted to the tropes and the figures that are modified and deteriorated by the language of passion called 'rhetoric of passion or psychological of figure', etc. And the third part interests in the body of the speech being the character of l' heart. Under the influence of the rhetoric of Lamy, French rhetoric at the 17th century is held for an essential text when one interests in the history of the ideas and rhetoric, marked in its specificity (passion). The project of Lamy registered in the concept of passion like 'manners of speaking'. To close this study, which does one have to retain? The first remark to note is that Lamy founds his rhetoric in opposition to traditional designs dating from the beginning of Aristote. Second remark is the idea that one finds based in famous the books of Dumarsais at the 18th century and Fontanier at the 19th century. Admittedly, Lamy is a true rhetorician, grammairien which interests in the question of passions in the speech forces to reconsider the idea spread since Mr. Foucault, and makes it possible to understand the passage of the Great century at the Century of Lumuères. Even if this opinion is not shared, it will be agreed that the work of Lamy on passions or the phenomena sensory and psychological in the center of the language deserves reflexion.
Journal of the Korean Society of Clothing and Textiles
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v.34
no.2
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pp.226-241
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2010
This study details the history and characteristics of consumption values, text style analyses, and appeal types expressed in magazine commercials from 1955 to 2008. This study analyzes the level of the social structure of commercial expression for each period. Consumption values based on the categories of consumption values by Sheth (1991) were classified through a total commercials analysis. Analyses on closing types of sentences, types of sentences, and rhetorical figures were executed focusing on headline text and text style. Appealing types were composed of rational, emotional, and ethical appeals. For analysis, the crosstab analysis and chi-square test of SPSS are used. The results are as follow. Seven values were constructed, functional value, social value, emotional value, conditional value, epistemic value, fashionable value, and indistinct value. The ratio of emotional value was the highest and functional value, epistemic value conditional value, fashionable value, social value, and indistinct value followed. The emotional value social value, conditional value, fashionable value, and epistemic value that focused on the emotion of consumers increased, while the functional value decreased. Sentences that use narrative styles, hyperboles, and metaphors that increased the interest of readers were dominantly used in the headline texts. For sentence expression, a declarative sentence in a sentence type, exciting curiosity in the expression method where hyperbole and figures of speech in rhetorical expressions are used most often. Emotional appeal was used almost twice more than the reasonable appeal for appeal types of the total commercial. The lower level of reasonable appeal is information that provides the product function. Interest and expression (such as pleasure and achievement) were used most often for emotional appeal. These results show that the most important issue is the emotional value in consumption in understanding the consumer. Marketing managers should also be aware of the functional value as well as an emotional value.
Some spoken word errors that violate grammatical or writing rules occurs frequently in communication environments like mobile phone and messenger. These unexpected errors cause a problem in a language processing system for many applications like speech recognition, text-to-speech translation, and so on. In this paper, we proposed and implemented an automatic correction system of ill-formed words and word spacing errors in SMS sentences that has been the major errors of poor accuracy. We experimented three methods of constructing the word correction dictionary and evaluated the results of those methods. They are (1) manual construction of error words from the vocabulary list of ill-formed communication languages, (2) automatic construction of error dictionary from the manually constructed corpus, and (3) context-dependent method of automatic construction of error dictionary.
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