• Title/Summary/Keyword: Words Error

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Error Correction and Praat Script Tools for the Buckeye Corpus of Conversational Speech (벅아이 코퍼스 오류 수정과 코퍼스 활용을 위한 프랏 스크립트 툴)

  • Yoon, Kyu-Chul
    • Phonetics and Speech Sciences
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    • v.4 no.1
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    • pp.29-47
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    • 2012
  • The purpose of this paper is to show how to convert the label files of the Buckeye Corpus of Spontaneous Speech [1] into Praat format and to introduce some of the Praat scripts that will enable linguists to study various aspects of spoken American English present in the corpus. During the conversion process, several types of errors were identified and corrected either manually or automatically by the use of scripts. The Praat script tools that have been developed can help extract from the corpus massive amounts of phonetic measures such as the VOT of plosives, the formants of vowels, word frequency information and speech rates that span several consecutive words. The script tools can extract additional information concerning the phonetic environment of the target words or allophones.

Implementation of Korean Error Correction System (한국어 오류 교정 시스템의 구현)

  • Choi, Jae-hyuk;Kim, Kweon-yang
    • The Journal of Korean Association of Computer Education
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    • v.3 no.2
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    • pp.115-127
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    • 2000
  • Korean error detectors of word processors have defects such as inconvenience that users choose one of error groups, lower detecting rate of 60%, and slow processing time. In this study, I proposed a resolution method of these defects. For these, I applied bidirectional longest match strategy for morphological analysis to improve processing time. I suggested dictionaries and several algorithms such as seperation of compound noun and assistant declinable words, correction of typing error to improve processing time and to guarantee correction accuracy. I also suggested a distinguishable method for dependent noun/suffix and Josa/Eomi where many ambiguities are generated, and a distinguishable method for Korean "로써/로서" to improve the reliability of the correction system.

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Improved block-wise MET for estimating vibration fields from the sensor

  • Jung, Byung Kyoo;Jeong, Weui Bong;Cho, Jinrae
    • Structural Engineering and Mechanics
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    • v.64 no.3
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    • pp.279-285
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    • 2017
  • Modal expansion technique (MET) is a method to estimate the vibration fields of flexible structures by using eigenmodes of the structure and the signals of sensors. It is the useful method to estimate the vibration fields but has the truncation error since it only uses the limit number of the eigenmodes in the frequency of interest. Even though block-wise MET performed frequency block by block with different valid eigenmodes was developed, it still has the truncation error due to the absence of other eigenmodes. Thus, this paper suggested an improved block-wise modal expansion technique. The technique recovers the truncation errors in one frequency block by utilizing other eigenmodes existed in the other frequency blocks. It was applied for estimating the vibration fields of a cylindrical shell. The estimated results were compared to the vibration fields of the forced vibration analysis by using two indices: the root mean square error and parallelism between two vectors. These indices showed that the estimated vibration fields of the improved block-wise MET more accurately than those of the established METs. Especially, this method was outstanding for frequencies near the natural frequency of the highest eigenmode of each block. In other words, the suggested technique can estimate vibration fields more accurately by recovering the truncation errors of the established METs.

Error Analysis of Writing in Elementary School Students (초등학생 작문 실태 분석 -낱말 형태 오류를 중심으로)

  • Lee, Chang-Keun
    • Journal of Digital Convergence
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    • v.11 no.3
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    • pp.381-387
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    • 2013
  • This study is the analysis of the form of the word appeared in the sixth grade of elementary school students' writing errors. The major findings of this study are as follows. 14532 words appeared, the average is 145.3. And 1903 sentences, and average 19.0 papers. On average, one sentence have consisted of 7.6 word. Second, the 69 people out of 100 had an error. This is serious. Because this study contains very basic contents. Third, the order of errors are abbreviations(33.09%), endings(27.70%), etc(19.78%), stems(19.42%). The results of this study can contribute to revise a elementary school textbooks. And the results of this study can contribute to select the contents of elementary spelling teaching.

Recognizing Unknown Words and Correcting Spelling errors as Preprocessing for Korean Information Processing System (한국어 정보처리 시스템의 전처리를 위한 미등록어 추정 및 철자 오류의 자동 교정)

  • Park, Bong-Rae;Rim, Hae-Chang
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.10
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    • pp.2591-2599
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    • 1998
  • In this paper, we proose a method of recognizing unknown words and correcting spelling errors(including spacing erors) to increase the performance of Korean information processing systems. Unknown words are recognized through comparative analysis of two or more morphologically similar eojeols(spacing units in Korean) including the same unknown word candidates. And spacing errors and spelling errors are corrected by using lexicatlized rules shich are automatically extracted from very large raw corpus. The extractionof the lexicalized rules is based on morphological and contextual similarities between error eojeols and their corection eojeols which are confirmed to be used in the corpus. The experimental result shows that our system can recognize unknown words in an accuracy of 98.9%, and can correct spacing errors and spelling errors in accuracies of 98.1% and 97.1%, respectively.

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Sentiment Prediction using Emotion and Context Information in Unstructured Documents (비정형 문서에서 감정과 상황 정보를 이용한 감성 예측)

  • Kim, Jin-Su
    • Journal of Convergence for Information Technology
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    • v.10 no.10
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    • pp.40-46
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    • 2020
  • With the development of the Internet, users share their experiences and opinions. Since related keywords are used witho0ut considering information such as the general emotion or genre of an unstructured document such as a movie review, the sensitivity accuracy according to the appropriate emotional situation is impaired. Therefore, we propose a system that predicts emotions based on information such as the genre to which the unstructured document created by users belongs or overall emotions. First, representative keyword related to emotion sets such as Joy, Anger, Fear, and Sadness are extracted from the unstructured document, and the normalized weights of the emotional feature words and information of the unstructured document are trained in a system that combines CNN and LSTM as a training set. Finally, by testing the refined words extracted through movie information, morpheme analyzer and n-gram, emoticons, and emojis, it was shown that the accuracy of emotion prediction using emotions and F-measure were improved. The proposed prediction system can predict sentiment appropriately according to the situation by avoiding the error of judging negative due to the use of sad words in sad movies and scary words in horror movies.

Real-time Implementation of Speech and Channel Coder on a DSP Chip for Radio Communication System (무선통신 적용을 위한 단일 DSP칩상의 음성/채널 부호화기 실시간 구현)

  • Kim Jae-Won;Sohn Dong-Chul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.6
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    • pp.1195-1201
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    • 2005
  • This paper deals with procedures and results for teal time implementation of G.729 speech coder and channel coder including convolution codec, viterbi decoder, and interleaver using a fixed point DSP chip for radio communication systems. We described the method for real-time implementation based on integer simulation results and explained the implemented results by quality performance and required complexity for real-time operation. The required complexity was 24MIPS and 9MIPS in computational load, and 12K words and 4K words in execution code length for speech and channel. The functional evaluation was performed into two steps. The one was bit exact comparison with a fixed point C code, the other was executed by actual speech samples and error test vectors. Unlik other results such as individual implementation, We implemented speech and channel coders on a DSP chip with 160MIPS computation capability and 64 K words memory on chip. This results outweigh the conventional methods in the point of system complexity and implementation cost for radio communication system.

Analysis of Mistakes Made in Using Loan Words in Domestic Hairstyling-related Academic Papers (국내 헤어 논문 외래어 오류 실태 분석)

  • Lee, Young-a;Lee, Jae-sook
    • Journal of Digital Convergence
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    • v.17 no.1
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    • pp.449-456
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    • 2019
  • This study attempted to improve the quality of hairstyling-related studies and provide basic data for future studies on hairstyling terms through analysis of cosmetology-related loan words used in hairstyling theses among recent cosmetology papers. For data collection to derive valid conclusions, the signatures of a total of 1,980 academic papers collected after typing in the keyword 'Hair' at the Research Information Sharing Service (http://www.riss.kr) were analyzed. The results show that researchers in hairstyling seem not to pay close attention to the correct use of foreign loan words. Therefore, the study results would be very helpful to the development of future cosmetology studies. The correct notation and use of foreign loanwords should be further encouraged.

Isolated Words Recognition using Correlation VQ-HMM (상관성있는 VQ-HMM을 이용한 고립 단어 인식)

  • 이진수
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1993.06a
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    • pp.109-112
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    • 1993
  • In this paper, we propose the modified VQ, applied correlation between codewords in order to reduce the error rate due to personal and speakers' temporal variation. Such a modified VQ is used in the stage of preprocessing of HMM and the temporal variation is absorbed by nonlinear Decimation and Interpolation of vowel part that we obtain higher recognition rate than not so case. The objects of experiment are Korea 142 DDD regional names and we show that the proposed method increase the recognition rate.

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A GPD-BASED DISCRIMINATIVE TRAINING ALGORITHM FOR PREDICTIVE NEURAL NETWORK MODELS

  • Na, Kyung-Min;Rheem, Jae-Yeol;Ann, Sou-Guil
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06a
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    • pp.997-1002
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    • 1994
  • Predictive neural network models are powerful speech recognition models based on a nonlinear pattern prediction. Those models can effectively normalize the temporal and spatial variability of speech signals. But those models suffer from poor discrimination between acoustically similar words. In this paper, we propose a discriminative training algorithm for predictive neural network models based on a generalized probabilistic descent (GPD) algorithm and minimum classification error formulation (MCEF). The Evaluation of our training algorithm on ten Korean digits shows its effectiveness by 40% reduction of recognition error.

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