• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.17-25
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• 2023

This study examines the fundamental frequency(f0) distribution of 2,740 Korean speakers in a dialogue speech corpus. Praat and R were used for the collection and analysis of acoustical f0 data after removing extreme values considering the interquartile f0 range of the intonational phrases produced by each individual speaker. Results showed that the average f0 value of all speakers was 185 Hz and the median value was 187 Hz. The f0 data showed a positively skewed distribution of 0.11, and the kurtosis was -0.09, which is close to the normal distribution. The pitch values of daily conversations varied in the range of 238 Hz. Further examination of the male and female groups showed distinct median f0 values: 114 Hz for males and 199 Hz for females. A t-test between the two groups yielded a significant difference. The skewness representing the distribution shape was 1.24 for the male group and 0.58 for the female group. The kurtosis was 5.21 and 3.88 for the male and female groups, and the male group values appeared leptokurtic. A regression analysis between the median f0 and age yielded a slope of 0.15 for the male group and -0.586 for the female group, which indicated a divergent relationship. In conclusion, a normative f0 distribution of different Korean age and sex groups can be examined in the conversational speech corpus recorded by a massive number of participants. However, more rigorous data might be required to define a relation between age and f0 values.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.1-11
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• 2021

In this study, we introduce trends in and the future of digital personal assistants. Recently, digital personal assistants have begun to handle many tasks like humans by communicating with users in human language on smart devices such as smart phones, smart speakers, and smart cars. Their capabilities range from simple voice commands and chitchat to complex tasks such as device control, reservation, ordering, and scheduling. The digital personal assistants of the future will certainly speak like a person, have a person-like personality, see, hear, and analyze situations like a person, and become more human. Dialogue processing technology that makes them more human-like has developed into an end-to-end learning model based on deep neural networks in recent years. In addition, language models pre-trained from a large corpus make dialogue processing more natural and better understood. Advances in artificial intelligence such as dialogue processing technology will enable digital personal assistants to serve with more familiar and better performance in various areas.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.15-18
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• 2002

Prosodic features of speech are known to play an important role in the transmission of linguistic information in human conversation. Their roles in the transmission of para- and non- linguistic information are even much more. In spite of their importance in human conversation, from engineering viewpoint, research focuses are mainly placed on segmental features, and not so much on prosodic features. With the aim of promoting research works on prosody, a research project 'Prosody and Speech Processing' is now going on. A rough sketch of the project is first given in the paper. Then, the paper introduces several prosody-related research works, which are going on in our laboratory. They include, corpus-based fundamental frequency contour generation, speech rate control for dialogue-like speech synthesis, analysis of prosodic features of emotional speech, reply speech generation in spoken dialogue systems, and language modeling with prosodic boundaries.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.269-272
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• 2003

음성인식의 연구 대상은 낭독음성에서 대화음성으로 발전해가고 있다. 이를 위해서는 대량의 대화코퍼스가 필요하다. 그러나 아직 충분한 양의 대화코퍼스가 구축되어 있지 못하며 코퍼스의 주석 정보 또한 복잡하고 다양하게 표현하고 있어 효율적인 활용이 어렵다. 따라서 본 논문에서는 대화 영역으로 텔래뱅킹 영역을 설정하고 대화코퍼스를 구축하여 구축된 대화코퍼스의 주석 정보를 XML(Extensible Markup Language)로 표준화할 수 있도록 DTD(Document Type Definition)를 정의하여 문서 구조화하였다.

• Asia Pacific Journal of Corpus Research
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• v.4 no.2
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• pp.1-39
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• 2023

Recent research in usage-based Second Language Acquisition has provided new insights into second language (L2) learners' development of formulaic language (Wulff, 2019). The current study examines the use of phrase-frames, which are recurring sequences of words including one or more variable slots (e.g., it is * that), in written and oral production data from Asian learners of English across four proficiency levels (beginner, low-intermediate, high-intermediate, advanced) and native English speakers. The variability, predictability, and discourse functions of the most frequent 4-word phrase-frames from the written essay and spoken dialogue sub-corpora of the International Corpus Network of Asian Learners of English (ICNALE) were analyzed and then compared across groups and modes. The results revealed that while learners' phrase-frames in writing became more variable and unpredictable as proficiency increased, no clear developmental patterns were found in speaking, although all groups used more fixed and predictable phrase-frames than the reference group. Further, no developmental trajectories in the functions of the most frequent phrase-frames were found in both modes. Additionally, lower-level learners and the reference group used more variable phrase-frames in speaking, whereas advanced-level learners showed more variability in writing. This study contributes to a better understanding of the development of L2 phraseological competence.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.365-368
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• 2005

We propose a speech act analysis method for Korean dialogue using Support Vector Machines (SVM). We use a lexical form of a word, its part of speech (POS) tags, and bigrams of POS tags as sentence features and the contexts of the previous utterance as context features. We select informative features by Chi square statistics. After training SVM with the selected features, SVM classifiers determine the speech act of each utterance. In experiment, we acquired overall $90.54\%$ of accuracy with dialogue corpus for hotel reservation domain.

• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.162-166
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• 2008

본 연구는 말뭉치로부터 추출된 정보를 사용하여 대화 시스템에 필요한 과정들을 통합 처리하는 시스템을 제안한다. 기존 연구는 영역 확장 시 대화 시스템의 각 과정들을 위해 많은 노력이 필요하였지만, 제안하는 방법은 말뭉치를 사용하여 각 과정들을 통합적으로 업데이트함으로서 이 문제를 해결하고자 한다. 사용자 입력문장과 말뭉치의 각 문장들 간의 유사도 계산을 통하여 의미적으로 가장 유사한 말뭉치 문장의 정보를 이용하고, 시스템 응답에 필요한 정보를 선택한다. 또한, 문맥에 관련된 정보를 자동으로 추출하여 대화 관리를 위한 대화 전이 네트워크(network)를 생성한다. 따라서, 제안 시스템은 말뭉치의 추가 및 수정만으로 새로운 영역 확장과 관리에 용이한 구조를 갖는다. 실험으로 관찰한 제안된 시스템의 성능은 유사도 계산 만족도 약 77%, 시스템 응답의 적절성 약 84%로 충분히 작업 수행이 가능한 점수를 보여주었다.

• Phonetics and Speech Sciences
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• v.15 no.2
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• pp.21-29
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• 2023

This study investigates the transitional aspect of vowel harmony in Korean verbal conjugation. By observing the patterns of harmonic and disharmonic tokens of 42 verbal stems searched for in the National Institute of Korean Language (NIKL) Korean Dialogue Corpus 2020/2021, I found that disharmonic tokens appeared less than 0.1% of time, most of which consisted of an /a/-stem with a monosyllabic sentence-final suffix. It was noted that disharmonic pattern started to spread to other suffixes and possibly to /o/-stems. A simple perception test showed that the disharmonic forms might have originated from vowel reduction or undershoot. These results suggest that the ongoing change is accounted for from both the articulatory and perceptual perspectives.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.288-293
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• 2011

To resolve ambiguities in speech act classification, various machine learning models have been proposed over the past 10 years. In this paper, we review these machine learning models and present the results of experimental comparison of three representative models, namely the decision tree, the support vector machine (SVM), and the maximum entropy model (MEM). In experiments with a goal-oriented dialogue corpus in the schedule management domain, we found that the MEM has lighter hardware requirements, whereas the SVM has better performance characteristics.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.630-632
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• 2018

최근 딥러닝(Deep Learning)기반 연구가 활발해짐에 따라 딥러닝 모델 기반의 대화 시스템 연구가 활성화되고 있다. 하지만 이러한 연구는 다량의 데이터를 기반으로 이루어지기 때문에 데이터 구축 연구의 필요성이 증가하고 있다. 기존에 공개된 대화 코퍼스는 대부분 영어로 이루어져있어 한국어 대화 시스템에는 적용하기 어렵다. 본 논문에서는 한국어 대화 코퍼스 구축을 위하여 식당예약 및 추천을 위한 한국어 대화를 수집하였으며, 총 498개의 대화를 수집하였다. 대화는 식당 예약 및 추천을 위한 12개의 정보를 수집할 수 있도록 구성하였다. 또한 데이터의 활용성을 높이기 위하여 데이터 후처리 작업으로 12개의 정보를 태깅작업을 하였다.