• Asia Pacific Journal of Corpus Research
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• v.2 no.1
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• pp.13-22
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• 2021

The present study employed an analytical framework that is characterised by a synthesis of quantitative and qualitative analyses with a specially designed computer software SpeechActConc to examine speech acts in business communication. The naturally occurring data from the audio recordings and the prosodic transcriptions of the business sub-corpora of the HKCSE (prosodic) are manually annotated with a speech act taxonomy for finding out the frequency of fillers, the co-occurring patterns of fillers with other speech acts, and the linguistic realisations of fillers. The discoursal function of fillers to sustain the discourse or to hold the floor has diverse linguistic realisations, ranging from a sound (e.g. 'uhuh') and a word (e.g. 'well') to sounds (e.g. 'um er') and words, namely phrase ('sort of') and clause (e.g. 'you know'). Some are even combinations of sound(s) and word(s) (e.g. 'and um', 'yes er um', 'sort of erm'). Among the top five frequent linguistic realisations of fillers, 'er' and 'um' are the most common ones found in all the six genres with relatively higher percentages of occurrence. The remaining more frequent realisations consist of clause ('you know'), word ('yeah') and sound ('erm'). These common forms are syntactically simpler than the less frequent realisations found in the genres. The co-occurring patterns of fillers and other speech acts are diverse. The more common co-occurring speech acts with fillers include informing and answering. The findings show that fillers are not only frequently used by speakers in spontaneous conversation but also mostly represented in sounds or non-linguistic realisations.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.63-70
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• 2006

In general, a corpus contains lots of linguistic information and is widely used in the field of natural language processing and computational linguistics. The creation of such the corpus, however, is an expensive, labor-intensive and time-consuming work. To alleviate this problem, annotation tools to build corpora with much linguistic information is indispensable. In this paper, we design and implement an annotation tool for establishing a Korean dependency tree-tagged corpus. The most ideal way is to fully automatically create the corpus without annotators' interventions, but as a matter of fact, it is impossible. The proposed tool is semi-automatic like most other annotation tools and is designed to edit errors, which are generated by basic analyzers like part-of-speech tagger and (partial) parser. We also design it to avoid repetitive works while editing the errors and to use it easily and friendly. Using the proposed annotation tool, 10,000 Korean sentences containing over 20 words are annotated with dependency structures. For 2 months, eight annotators have worked every 4 hours a day. We are confident that we can have accurate and consistent annotations as well as reduced labor and time.

• MALSORI
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• no.66
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• pp.87-103
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• 2008

We describe a new active learning method in conditional random fields (CRFs) framework for keyphrase extraction. To save elaboration in annotation, we use diversity and representative measure. We select high diversity training candidates by sentence confidence value. We also select high representative candidates by clustering the part-of-speech patterns of contexts. In the experiments using dialog corpus, our method achieves 86.80% and saves 88% training corpus compared with those of supervised method. From the results of experiment, we can see that the proposed method shows improved performance over the previous methods. Additionally, the proposed method can be applied to other applications easily since its implementation is independent on applications.

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.162-179
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• 2008

We have developed a tool for annotation of electronic health record (EHR) data. Currently we are in the process of manually annotating a corpus of Norwegian general practitioners' EHRs with mainly linguistic information. The purpose of this project is to attain a linguistically annotated corpus of patient histories from general practice. This corpus will be put to future use in medical language processing and information extraction applications. The paper outlines some of our practical experiences from developing such a corpus and, in particular, the effects of semi-automated annotation. We have also done some preliminary experiments with part-of-speech tagging based on our corpus. The results indicated that relevant training data from the clinical domain gives better results for the tagging task in this domain than training the tagger on a corpus form a more general domain. We are planning to expand the corpus annotations with medical information at a later stage.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.224-231
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• 2013

Defining the concept of prominent audio content as the most informative audio content from the users' perspective within a given unstructured audio segment, we propose a simple but robust intensity-based attack/release pattern features to detect the prominent audio content. We also propose a web-based annotation procedure to retrieve users' subjective perception and annotated 18 hours of video clips across various genres, such as cartoon, movie, news, etc. The experiments with a linear classification method whose models are trained for speech, music, and sound effect demonstrate promising - but varying across the genres of programs - results (e.g., 86.7% weighted accuracy for speech-oriented talk shows and 49.3% weighted accuracy for {action movies}).

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.171-181
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• 2007

Ubiquitous computing is a vision of our future computing lifestyle in which computer systems seamlessly integrate into our everyday lives, providing services and information in anywhere and anytime fashion. Augmented reality (AR) can naturally complement ubiquitous computing by providing an intuitive and collaborative visualization and simulation interface to a three-dimensional information space embedded within physical reality. This paper presents a service framework and its applications for providing context-aware u-car maintenance services using augmented reality, which can support a rich set of ubiquitous services and collaboration. It realizes bi-augmentation between physical and virtual spaces using augmented reality. It also offers a context processing module to acquire, interpret and disseminate context information. In particular, the context processing module considers user's preferences and security profile for providing private and customer-oriented services. The prototype system has been implemented to support 3D animation, TTS (Text-to-Speech), augmented manual, annotation, and pre- and post-augmentation services in ubiquitous car service environments.

• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.191-196
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• 2009

본 논문에서는 자바 기반의 품사부착 코퍼스 작성 도구를 제안 및 구현한다. 본 시스템에서는 각 사용자가 독립적으로 실행하지만 주요 데이터베이스는 서버에서 관리함으로서 지식을 공유할 수 있고, 품사부착 작업에 있어 사전에 만들어진 어절 후보로부터의 선택 및 사용자 입력이 가능하도록 한다. 고빈도 오류어절의 자동 표시 기능, 용례 검색을 통한 도움말 기능, 코멘트를 기반으로 구성된 집단 지식을 이용한 도움말 확장 기능 및 사전 검색 기능을 구현한다. 또한, 일관성 검사를 통해 품사부착 결과에 대한 신뢰도 증가 및 작업의 편의성을 증대시킬 수 있도록 설계한다.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.3-23
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• 2007

King Sejong the Great, his students in Jip-hyeun-jeon school and Choe Sejin, their successor of the sixteenth century, indicated Middle Korean had three distinctive pitches, low, high, and rising (phyeong-, geo-, sang-sheong). Thanks to $Hun-min-jeng-{\emptyset}eum$ as well as its Annotation and side-dots literatures in fifteenth and sixteenth centuries, we can compare Middle Korean with Hamgyeong dialect, Gyeongsang dialect, and extant tone dialects with joint preservers of what was probably the tonal system of unitary mother Korean language. What is most remarkable about middle Korean phonetic work is its manifest superiority in conception and execution as anything produced in the present day linguistic scholarship. But at this stage in linguistics, prior to the technology and equipment needed for the scientific analysis of sound waves, auditory description was the only possible frame for an accurate and systematic classification. And auditory phonetics still remains fundamental in pitch description, even though modern acoustic categories may supplement and supersede auditory ones in tonological analysis. Auditory phonetics, however, has serious shortcoming that its theory and practice are too subject to be developed into the present century science. With joint researchers, I am developping a new pitch scale. It is a semiautomatic auditory grade pitch analysis program. The result of our labor will give a significant breakthrough to upgrade our component in linguistics.

• Proceedings of the IEEK Conference
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• summer
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• pp.103-109
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• 2004

In NLP (Natural Language Processing) tasks, the highest difficulty which computers had to face with, is the built-in ambiguity of Natural Languages. To disambiguate it, formerly, they based on human-devised rules. Building such a complete rule-set is time-consuming and labor-intensive task whilst it doesn't cover all the cases. Besides, when the scale of system increases, it is very difficult to control that rule-set. So, recently, many NLP tasks have changed from rule-based approaches into corpus-based approaches with large annotated corpora. Corpus-based NLP tasks for such popular languages as English, French, etc. have been well studied with satisfactory achievements. In contrast, corpus-based NLP tasks for Vietnamese are at a deadlock due to absence of annotated training data. Furthermore, hand-annotation of even reasonably well-determined features such as part-of-speech (POS) tags has proved to be labor intensive and costly. In this paper, we present our building an annotated English-Vietnamese parallel aligned corpus named EVC to train for Vietnamese-related NLP tasks such as Word Segmentation, POS-tagger, Word Order transfer, Word Sense Disambiguation, English-to-Vietnamese Machine Translation, etc.