• Title/Summary/Keyword: Word Input

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SOC Verification Based on WGL

  • Du, Zhen-Jun;Li, Min
    • Journal of Korea Multimedia Society
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    • v.9 no.12
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    • pp.1607-1616
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    • 2006
  • The growing market of multimedia and digital signal processing requires significant data-path portions of SoCs. However, the common models for verification are not suitable for SoCs. A novel model--WGL (Weighted Generalized List) is proposed, which is based on the general-list decomposition of polynomials, with three different weights and manipulation rules introduced to effect node sharing and the canonicity. Timing parameters and operations on them are also considered. Examples show the word-level WGL is the only model to linearly represent the common word-level functions and the bit-level WGL is especially suitable for arithmetic intensive circuits. The model is proved to be a uniform and efficient model for both bit-level and word-level functions. Then Based on the WGL model, a backward-construction logic-verification approach is presented, which reduces time and space complexity for multipliers to polynomial complexity(time complexity is less than $O(n^{3.6})$ and space complexity is less than $O(n^{1.5})$) without hierarchical partitioning. Finally, a construction methodology of word-level polynomials is also presented in order to implement complex high-level verification, which combines order computation and coefficient solving, and adopts an efficient backward approach. The construction complexity is much less than the existing ones, e.g. the construction time for multipliers grows at the power of less than 1.6 in the size of the input word without increasing the maximal space required. The WGL model and the verification methods based on WGL show their theoretical and applicable significance in SoC design.

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A Word Sense Disambiguation Method with a Semantic Network (의미네트워크를 이용한 단어의미의 모호성 해결방법)

  • DingyulRa
    • Korean Journal of Cognitive Science
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    • v.3 no.2
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    • pp.225-248
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    • 1992
  • In this paper, word sense disambiguation methods utilizing a knowledge base based on a semantic network are introduced. The basic idea is to keep track of a set of paths in the knowledge base which correspond to the inctemental semantic interpretation of a input sentence. These paths are called the semantic paths. when the parser reads a word, the senses of this word which are not involved in any of the semantic paths are removed. Then the removal operation is propagated through the knowledge base to invoke the removal of the senses of other words that have been read before. This removal operation is called recusively as long as senses can be removed. This is called the recursive word sense removal. Concretion of a vague word's concept is one of the important word sense disambiguation methods. We introduce a method called the path adjustment that extends the conctetion operation. How to use semantic association or syntactic processing in coorporation with the above methods is also considered.

Sentence Rejection using Word Spotting Ratio in the Phoneme-based Recognition Network (음소기반 인식 네트워크에서의 단어 검출률을 이용한 문장거부)

  • Kim, Hyung-Tai;Ha, Jin-Young
    • Proceedings of the KSPS conference
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    • 2005.04a
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    • pp.99-102
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    • 2005
  • Research efforts have been made for out-of-vocabulary word rejection to improve the confidence of speech recognition systems. However, little attention has been paid to non-recognition sentence rejection. According to the appearance of pronunciation correction systems using speech recognition technology, it is needed to reject non-recognition sentences to provide users with more accurate and robust results. In this paper, we introduce standard phoneme based sentence rejection system with no need of special filler models. Instead we used word spotting ratio to determine whether input sentences would be accepted or rejected. Experimental results show that we can achieve comparable performance using only standard phoneme based recognition network in terms of the average of FRR and FAR.

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A Study on Korean Spoken Language Understanding Model (한국어 구어 음성 언어 이해 모델에 관한 연구)

  • 노용완;홍광석
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2435-2438
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    • 2003
  • In this paper, we propose a Korean speech understanding model using dictionary and thesaurus. The proposed model search the dictionary for the same word with in input text. If it is not in the dictionary, the proposed model search the high level words in the high level word dictionary based on the thesaurus. We compare the probability of sentence understanding model with threshold probability, and we'll get the speech understanding rate. We evaluated the performance of the sentence speech understanding system by applying twenty questions game. As the experiment results, we got sentence speech understanding accuracy of 79.8%. In this case probability of high level word is 0.9 and threshold probability is 0.38.

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Isolated-Word Recognition Using Adaptively Partitioned Multisection Codebooks (음성적응(音聲適應) 구간분할(區間分割) 멀티섹션 코드북을 이용(利用)한 고립단어인식(孤立單語認識))

  • Ha, Kyeong-Min;Jo, Jeong-Ho;Hong, Jae-Kuen;Kim, Soo-Joong
    • Proceedings of the KIEE Conference
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    • 1988.07a
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    • pp.10-13
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    • 1988
  • An isolated-word recognition method using adaptively partitioned multisection codebooks is proposed. Each training utterance was divided into several sections according to its pattern extracted by labeling technique. For each pattern, reference codebooks were generated by clustering the training vectors of the same section. In recognition procedure, input speech was divided into the sections by the same method used in codebook generation procedure, and recognized to the reference word whose codebook represented the smallest average distortion. The proposed method was tested for 100 Korean words and attained recognition rate about 96 percent.

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Isolated word recognition using the SOFM-HMM and the Inertia (관성과 SOFM-HMM을 이용한 고립단어 인식)

  • 윤석현;정광우;홍광석;박병철
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.6
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    • pp.17-24
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    • 1994
  • This paper is a study on Korean word recognition and suggest the method that stabilizes the state-transition in the HMM by applying the `inertia' to the feature vector sequences. In order to reduce the quantized distortion considering probability distribution of input vectors, we used SOFM, an unsupervised learning method, as a vector quantizer, By applying inertia to the feature vector sequences, the overlapping of probability distributions for the response path of each word on the self organizing feature map can be reduced and the state-transition in the Hmm can be Stabilized. In order to evaluate the performance of the method, we carried out experiments for 50 DDD area names. The results showed that applying inertia to the feature vector sequence improved the recognition rate by 7.4% and can make more HMMs available without reducing the recognition rate for the SOFM having the fixed number of neuron.

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Research on the Automatic Software Keyboard Based on Database (데이터베이스에 근거한 자동 키보드의 입력 방법)

  • Lee Kye Suk;Yong Hwan Seung
    • Journal of Korea Multimedia Society
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    • v.8 no.1
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    • pp.101-110
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    • 2005
  • Recently software keyboard is widely used in mobile devices where restrictive hardware keyboard is available. In this paper, new software-driven keyboard input method is proposed, which use minimum number of keyboard input with small keyboard space generated after analyzing of database. In this software keyboard is generated dynamically at each input step by analyzing all possible input words. Software keyboard, only possible key buttons are displayed for minimizing keyboard space and preventing mistyping. And it also provide input word completion function when the number of the candidate words is within threshold scope.

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A Study on the input butter for efficient processing of MPEG Audio bitstream (MPEG Audio 비트스트림의 효율적 처리를 위한 입력 버퍼에 관한 연구)

  • 임성룡;공진흥
    • Proceedings of the IEEK Conference
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    • 2000.06b
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    • pp.181-184
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    • 2000
  • In this paper, we described a design of the input buffer system for efficiently dealing with MPEG audio bitstream to demux header and side information, audio data. In order to overcome the limitations of fixed-word manipulation in bitstream demuxing, we proposed a new variable length bit retrieval system with FSM sequencer supporting MPEG audio frame format, and serial buffer demuxing audio stream, FIFO circular buffer including header and side information.

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A Study on Implementation of a VXIbus System Using Shared Memory Protocol (공유메모리 프로토콜을 이용한 VXIbus 시스템 구현에 관한 연구)

  • 노승환;강민호;김덕진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.9
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    • pp.1332-1347
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    • 1993
  • Existing instruments are composed independently according to their function and user constructed instrumentation system with those instruments. But in the late 1980s VXI bus enables to construct instrumentation system with various modular type instruments. For an VXI bus system with the word serial protocol, an increase of data size can degrade the system performance. In this paper shared memory protocol is proposed to overcome performance degradation. The shared memory protocol is analyzed using the GSPN and compared with that of the word serial protocol. It is shown that the shared memory protocol has a better performance than the word serial protocol. The VXI bus message based-system with the proposed shared memory protocol is constructed and experimented with signal generating device and FFT analyzing device. Up to 80 KHz input signal the result of FFT analysis is accurate and that result is agree with that of conventional FFT analyzer. In signal generating experiment from 100 KHz to 1.1 GHz sine wave is generated.

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A Comparison of Two Methods of Instruction on Mathematical Word Problem (교수 중재 방법에 따른 수학 문장제 수행 비교)

  • Kim, Euk-Gon
    • School Mathematics
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    • v.11 no.3
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    • pp.497-511
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    • 2009
  • This study compared two problem solving instructional approaches, schema based sequence instruction and schema based parallel instruction on word problem solving performance of elementary school students who were in general students group. The subjects totaled 48 third grade students who were exposed to a test that consisted of 9 word problem items of three types for 4 sessions. First of all, the baseline of word problem performance level was measured without any training. During session 1, 2 and 3 participants were put into strategic training groups. The experiment was designed by two between factor(two intervention group and two within factors(two problem types, three sessions). The results of experiment were as follows. Schema based sequence instruction group performed significantly better than students in another group on word problem solving performance. The effect of strategic schema based Instruction revealed that solving word problems relied upon problem types, sessions and input orders which were of great value.

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