• Title/Summary/Keyword: Sentence Analysis

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Lattice-based Discriminative Approach for Korean Morphological Analysis (래티스상의 구조적 분류에 기반한 한국어 형태소 분석 및 품사 태깅)

  • Na, Seung-Hoon;Kim, Chang-Hyun;Kim, Young-Kil
    • Journal of KIISE:Software and Applications
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    • v.41 no.7
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    • pp.523-532
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    • 2014
  • In this paper, we propose a lattice-based discriminative approach for Korean morphological analysis and POS tagging. In our approach, for an input sentence, a morpheme lattice is first created from a lexicon where each node corresponds to a morpheme in the lexicon and each edge is formed between two consecutive morphemes. A candidate result of morphological analysis is then represented as a path in the morpheme lattice which is defined as the sequence of edges, starting in the initial state and ending with the final state. In this setting, the morphological analysis is simply considered as the process of finding the best path among all possible paths. Experiment results show that the proposed lattice-based method outperforms the first-order linear-chain CRF.

Music Structure Analysis and Application (악곡구조 분석과 활용)

  • Seo, Jung-Bum;Bae, Jae-Hak
    • The KIPS Transactions:PartB
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    • v.14B no.1 s.111
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    • pp.33-42
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    • 2007
  • This paper presents a new methodology for music structure analysis which facilitates rhetoric-based music summarization. Similarity analysis of musical constituents suggests the structure of a musical piece. We can recognize its musical form from the structure. Musical forms have rhetorical characteristics of their on. We have utilized the characteristics for locating musical motifs. Motif extraction is to music summarization what topic sentence extraction is to text summarization. We have evaluated the effectiveness of this methodology through a popular music case study.

A Study on the Psychological Counseling AI Chatbot System based on Sentiment Analysis (감정분석 기반 심리상담 AI 챗봇 시스템에 대한 연구)

  • An, Se Hun;Jeong, Ok Ran
    • Journal of Information Technology Services
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    • v.20 no.3
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    • pp.75-86
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    • 2021
  • As artificial intelligence is actively studied, chatbot systems are being applied to various fields. In particular, many chatbot systems for psychological counseling have been studied that can comfort modern people. However, while most psychological counseling chatbots are studied as rule-base and deep learning-based chatbots, there are large limitations for each chatbot. To overcome the limitations of psychological counseling using such chatbots, we proposes a novel psychological counseling AI chatbot system. The proposed system consists of a GPT-2 model that generates output sentence for Korean input sentences and an Electra model that serves as sentiment analysis and anxiety cause classification, which can be provided with psychological tests and collective intelligence functions. At the same time as deep learning-based chatbots and conversations take place, sentiment analysis of input sentences simultaneously recognizes user's emotions and presents psychological tests and collective intelligence solutions to solve the limitations of psychological counseling that can only be done with chatbots. Since the role of sentiment analysis and anxiety cause classification, which are the links of each function, is important for the progression of the proposed system, we experiment the performance of those parts. We verify the novelty and accuracy of the proposed system. It also shows that the AI chatbot system can perform counseling excellently.

Aspect-based Sentiment Analysis of Product Reviews using Multi-agent Deep Reinforcement Learning

  • M. Sivakumar;Srinivasulu Reddy Uyyala
    • Asia pacific journal of information systems
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    • v.32 no.2
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    • pp.226-248
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    • 2022
  • The existing model for sentiment analysis of product reviews learned from past data and new data was labeled based on training. But new data was never used by the existing system for making a decision. The proposed Aspect-based multi-agent Deep Reinforcement learning Sentiment Analysis (ADRSA) model learned from its very first data without the help of any training dataset and labeled a sentence with aspect category and sentiment polarity. It keeps on learning from the new data and updates its knowledge for improving its intelligence. The decision of the proposed system changed over time based on the new data. So, the accuracy of the sentiment analysis using deep reinforcement learning was improved over supervised learning and unsupervised learning methods. Hence, the sentiments of premium customers on a particular site can be explored to other customers effectively. A dynamic environment with a strong knowledge base can help the system to remember the sentences and usage State Action Reward State Action (SARSA) algorithm with Bidirectional Encoder Representations from Transformers (BERT) model improved the performance of the proposed system in terms of accuracy when compared to the state of art methods.

Verification of the Usefulness of the Mock TOEIC Test using Corpus Indices : Focusing on the Analysis of Difficulty and Discrimination (코퍼스 지표를 활용한 모의 토익시험의 유용성 검증 : 난이도와 변별도 분석을 중심으로)

  • Lee, Yena
    • The Journal of the Korea Contents Association
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    • v.21 no.10
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    • pp.576-593
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    • 2021
  • In this study, in order to investigate the factors that affect the percentage of correct answers and the degree of discrimination of the TOEIC test, a regression analysis was performed using corpus indicators that influence correct answer rate and the degree of discrimination for each part derived from the item analysis. The basic calculation word_length, consistency index LSA_overlap_adjacent_sentences, lexical diversity MTLD_VOCD, conjunction All_logical_causal_connectives_incidence, situational model casual_particles_causal_verbs_Ratio, syntactic complexity Left_embeddedness, and syntactic pattern density Infinitive_density were found to have negative effects. These factors that lower the correct answer rate can be utilized when setting learning goals. Vocabulary diversity index MTLD_VOCD, conjunction Additive_connectives_incidence, syntactic pattern density Infinitive_density, and lexical information person1_2_pronoun_incidence were found to have a positive effect. Factors influencing the increase in discrimination may provide important information for developing a learning program.

The Acoustic Analysis of Korean Read Speech - with respect to the prosodic phrasing - (한국어 낭독체 문장의 음향분석 -바람과 햇님의 운율구 생성을 중심으로-)

  • Sung Chuljae
    • Proceedings of the KSPS conference
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    • 1996.02a
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    • pp.157-172
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    • 1996
  • This study aims to suggest some theoretical methodology for analysis of the prosodic patterns in Korean Read Speech. The engineering effort relevant to the phonetic study has focused to the importance of prosodic phrasing which may play a major role in analyzing the phonetic DB. Before establishing the prosodic phrase as the prosodic unit, we should describe the features of the boundary signal in a target sentence. With this in mind, the general characteristics of Read Speech and the ToBI(tones and Break Indices), which has been currently in vogue with respect to the prosodic labelling system were presented as the first step. The concrete analysis was carried out with the fable 'North Wind and the Sun' Korean version, where about 25 prosodic units were discriminated by perceptual approach for 5 subjects. Establishing various informations which can be used for deciding a boundary position systematically, we can proceed to the next, viz. acoustic analysis of prosodic unit. The most important which we primarily study for improving the naturalness of synthetic speech may be, at first, detecting the boundary signals in the speech file and accordingly reestablishment it within the raw text.

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The Loom-LAG for syntax analysis Adding a language-independent level to LAG

  • Schulze, Markus
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2002.02a
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    • pp.411-420
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    • 2002
  • The left-associative grammar model (LAG) has been applied successfully to the morphologic and syntactic analysis of various european and asian languages. The algebraic definition of the LAG is very well suited for the application to natural language processing as it inherently obeys de Saussure's second law (de Saussure, 1913, p. 103) on the linear nature of language, which phrase-structure grammar (PSG) and categorial grammar (CG) do not. This paper describes the so-called Loom-LAGs (LLAG) -a specialization of LAGs for the analysis of natural language. Whereas the only means of language-independent abstraction in ordinary LAG is the principle of possible continuations, LLAGs introduce a set of more detailed language-independent generalizations that form the so-called loom of a Loom-LAG. Every LLAG uses the very smut loom and adds the language-specific information in the form of a declarative description of the language -much like an ancient mechanised Jacquard-loom would take a program-card providing the specific pattern for the cloth to be woven. The linguistic information is formulated declaratively in so-called syntax plans that describe the sequential structure of clauses and phrases. This approach introduces the explicit notion of phrases and sentence structure to LAG without violating de Saussure's second law iud without leaving the ground of the original algebraic definition of LAG, LLAGS can in fact be shown to be just a notational variant of LAG -but one that is much better suited for the manual development of syntax grammars for the robust analysis of free texts.

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Development of Japanese to Korean Machine Translation System ATOM Using Personal Computer I - Dictionary Construction and Morphological Analysis - (PC를 이용한 일$\cdot$한 번역 시스템 ATOM의 개발에 관한 연구 ( I ) - 구문해석과 생성과 사전 구성과 형태소 해석을 중심으로 -)

  • Kim, Young-Sum;Kim, Han-Woo;Choi, Byung-Uk
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.10
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    • pp.1183-1192
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    • 1988
  • In this paper, we describe heuristic information-added morphological dictionary and connection table, and automatic MUNJEUL separation process on the basis of least cost method for efficient morphological analysis. It is simplified the composition of connection and inflective word information by mutually interconnect conjugation table with connection tables. As a result, the applicability of system is increased. Translation dictionary consists of analysis and generation part and, increase the applicability by describing frequently using termination phrase which is extracted statistically as idiom and the procedure directly on the dictionary for the efficiency of analysis process and more natural generation of translation sentence.

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Cepstral and spectral analysis of voices with adductor spasmodic dysphonia (내전형연축성 발성장애 음성에 대한 켑스트럼과 스펙트럼 분석)

  • Shim, Hee Jeong;Jung, Hun;Lee, Sue Ann;Choi, Byung Heun;Heo, Jeong Hwa;Ko, Do-Heung
    • Phonetics and Speech Sciences
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    • v.8 no.2
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    • pp.73-80
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    • 2016
  • The purpose of this study was to analyze perceptual and spectral/cepstral measurements in patients with adductor spasmodic dysphonia(ADSD). Sixty participants with gender and age matched individuals(30 ADSD and 30 controls) were recorded in reading a sentence and sustained the vowel /a/. Acoustic data were analyzed acoustically by measuring CPP, L/H ratio, mean CPP F0 and CSID, and auditory-perceptual ratings were measured using GRBAS. The main results can be summarized as below: (a) the CSID for the connected speech was significantly higher than for the sustained vowel (b) the G, R and S for the connected speech were significantly higher than for the sustained vowel (c) Spectral/cepstral parameters were significantly correlated with the perceptual parameters, and (d) the ROC analysis showed that the threshold of 13.491 for the CSID achieved a good classification for ADSD, with 86.7% sensitivity and 96.7% specificity. Spectral and cepstral analysis for the connected speech is especially meaningful on cases where perceptual analysis and clinical evaluation alone are insufficient.

An Analysis of $H^*$ Production by Korean Learners of English according to the Focus of English Sentences in Comparison with Native Speakers of English and Its Pedagogical Implications (영어 원어민과 비교한 한국인 학습자의 영어 문장 초점에 따른 영어 고성조 구현의 분석과 억양교육에 대한 시사점)

  • Yi, So-Pae
    • Phonetics and Speech Sciences
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    • v.3 no.3
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    • pp.57-62
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    • 2011
  • Focused items in English sentences are usually accompanied by changes in acoustic manifestation. This paper investigates the acoustic characteristics of $H^*$ in English utterances produced by natives speakers of English and Korean learners of English. To obtain more reliable results, the changes of the acoustic feature values (F0, intensity, syllable duration) were normalized by a median value and a whole duration of each utterance. Acoustic values of sentences with no focused words were compared with those of sentences with focused words within each group (Americans vs. Koreans). Sentences with focused words were compared between the two groups, too. In the instances in which a significant Group x Focus Location (initial, middle and final of a sentence) interaction was obtained, further analysis testing the effect of Group on each Focus Location was conducted. The analysis revealed that Korean learners of English produced focused words with lower F0, lower intensity and shorter syllable duration than native speakers of English. However, the effect of intensity change caused by focus was not significant within each group. Further analysis examining the interaction of Group and Focus Location showed that the change in F0 produced by Korean group was significantly lower in the middle and the final positions of sentences than by American group. Implications for the intonation training were also discussed.

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