• Title/Summary/Keyword: 동적시간신축

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Speaker Identification Using Dynamic Time Warping Algorithm (동적 시간 신축 알고리즘을 이용한 화자 식별)

  • Jeong, Seung-Do
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.5
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    • pp.2402-2409
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    • 2011
  • The voice has distinguishable acoustic properties of speaker as well as transmitting information. The speaker recognition is the method to figures out who speaks the words through acoustic differences between speakers. The speaker recognition is roughly divided two kinds of categories: speaker verification and identification. The speaker verification is the method which verifies speaker himself based on only one's voice. Otherwise, the speaker identification is the method to find speaker by searching most similar model in the database previously consisted of multiple subordinate sentences. This paper composes feature vector from extracting MFCC coefficients and uses the dynamic time warping algorithm to compare the similarity between features. In order to describe common characteristic based on phonological features of spoken words, two subordinate sentences for each speaker are used as the training data. Thus, it is possible to identify the speaker who didn't say the same word which is previously stored in the database.

Enhancement of Ship's Wheel Order Recognition System using Speaker's Intention Predictive Parameters (화자의도예측 파라미터를 이용한 조타명령 음성인식 시스템의 개선)

  • Moon, Serng-Bae
    • Journal of Advanced Marine Engineering and Technology
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    • v.32 no.5
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    • pp.791-797
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    • 2008
  • The officer of the deck(OOD) may sometimes have to carry out lookout as well as handling of auto pilot without a quartermaster at sea. The purpose of this paper is to develop the ship's auto pilot control module using speech recognition in order to reduce the potential risk of one man bridge system. The feature parameters predicting the OOD's intention was extracted from the sample wheel orders written in SMCP(IMO Standard Marine Communication Phrases). We designed a pre-recognition procedure which could make some candidate words using DTW(Dynamic Time Warping) algorithm, a post-recognition procedure which made a final decision from the candidate words using the feature parameters. To evaluate the effectiveness of these procedures the experiment was conducted with 500 wheel orders.

Scalable scheduling techniques for distributed real-time multimedia database systems (분산 실시간 멀티미디어 데이터베이스 시스템을 위한 신축성있는 스케줄링 기법)

  • Kim, Jin-Hwan
    • The KIPS Transactions:PartA
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    • v.9A no.1
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    • pp.9-18
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    • 2002
  • In this paper, we propose scalable scheduling techniques based on EDF to efficiently integrate hard real-time and multimedia soft real-time tasks in the distributed real-time multimedia database system. Hard tasks are guarangteed based on worst case execution times, whereas multimedia soft tasks are served based on mean execution times. This paper describes a served-based scheme for partitioning the CPU bandwidth among different task classes that coexist in the same system. To handle the problem of class overloads characterized by varying number of tasks and varying task arrival rates, thus scheme shows how to adjust the fraction of the CPU bandwidth assigned to each class. This scheme fixes the maximum time that each hard task can execute in the period of the server, whereas it can dynamically change the bandwidth reserved to each multimedia task. The proposed method is capable of minimizing the mean tardiness of multimedia tasks, without jeopardizing the schedulability of the hard tasks. The performance of this scheduling method is compared with that of similar mechanisms through simulation experiments.

A Case-Specific Feature Weighting Method in Case-Based Reasoning (사례기반 추론에서 사례별 속성 가중치 부여 방법)

  • 이재식;전용준
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 1999.10a
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    • pp.391-398
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    • 1999
  • 사례기반 추론을 포함한 Lazy Learning 방법들은 인공신경망이나 의사결정 나무와 같은 Eager Learning 방법들과 비교하여 여러 가지 상대적인 장점을 가지고 있다. 그러나 Lazy Learning 방법은 역시 상대적인 단점들도 가지고 있다. 첫째로 사례를 저장하기 위하여 많은 공간이 필요하며, 둘째로 문제해결 시점에서 시간이 많이 소요된다. 그러나 보다 심각한 문제점은 사례가 관련성이 낮은 속성들을 많이 가지고 있는 경우에 Lazy Learning 방법은 사례를 비교할 때에 혼란을 겪을 수 있다는 점이며, 이로 인하여 분류 정확도가 크게 저하될 수 있다. 이러한 문제점을 해결하기 위하여 Lazy Learning 방법을 위한 속성 가중치 부여 방법들이 많이 연구되어 왔다. 그러나 기존에 발표된 대부분의 방법들이 속성 가중치의 유효 범위를 전역적으로 하는 것들이었다. 이에 본 연구에서는 새로운 지역적 속성 가중치 부여 방법을 제안한다. 본 연구에서 제안하는 속성 가중치 부여 방법(CBDFW : 사례기반 동적 속성 가중치 부여)은 사례별로 속성 가중치를 다르게 부여하는 방법으로서 사례기반 추론의 원리를 속성 가중치 부여 과정에 적용하는 것이다. CBDFW의 장점으로서 (1) 수행 방법이 간단하며, (2) 논리적인 처리 비용이 기존 방법들에 비해 낮으며, (3) 신축적이라는 점을 들 수 있다. 본 연구에서는 신용 평가 문제에 CBDFW의 적용을 시도하였고, 다른 기법들과 비교에서 비교적 우수한 결과를 얻었다.

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Effects of the Degree of GO Reduction on PC-GO Chemical Reactions and Physical Properties (그래핀 옥사이드(GO)의 환원정도가 PC-GO 화학반응 및 물성에 미치는 영향)

  • Park, Ju Young;Shin, Jin Hwan;Kim, Youn Cheol
    • Applied Chemistry for Engineering
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    • v.26 no.1
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    • pp.53-58
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    • 2015
  • Polycarbonate (PC)/graphene oxide (GO) composites with 3 phr of GO were prepared by using a twin screw extruder at 240, 260, and $280^{\circ}C$ after mixing the solution with chloroform. It was confirmed by DSC and TGA that the glass transition temperature ($T_g$) of PC/GO composites were not changed and the thermal stability was the best in case of the extrusion temperature at $260^{\circ}C$. Thermo mechanical properties of PC/GO composites according to extrusion temperatures were measured by dynamic mechanical analysis (DMA). Storage moduli of PC/GO composites were higher than that of pure PC and there was no detectable changes at varying the extrusion temperature. Based on these results, the extrusion temperature of PC/GO composites was fixed at $260^{\circ}C$. The degree of the chemical reaction of PC/GO composites with respect to the GO reduction time was confirmed by the C-H stretching peak at $3000cm^{-1}$ and the degree of the chemical reaction was similar to that of GO when the reduction time was 1 h. A decrease in the complex viscosity as a function of the GO reduction time was detected by dynamic rheometer, which may be originated from the enhancement of GO dispersion by PC-GO reaction. The GO dispersion was confirmed by scanning electron microscope (SEM).