• 제목/요약/키워드: text features

검색결과 577건 처리시간 0.029초

Speaker Verification Using Hidden LMS Adaptive Filtering Algorithm and Competitive Learning Neural Network (Hidden LMS 적응 필터링 알고리즘을 이용한 경쟁학습 화자검증)

  • Cho, Seong-Won;Kim, Jae-Min
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • 제51권2호
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    • pp.69-77
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    • 2002
  • Speaker verification can be classified in two categories, text-dependent speaker verification and text-independent speaker verification. In this paper, we discuss text-dependent speaker verification. Text-dependent speaker verification system determines whether the sound characteristics of the speaker are equal to those of the specific person or not. In this paper we obtain the speaker data using a sound card in various noisy conditions, apply a new Hidden LMS (Least Mean Square) adaptive algorithm to it, and extract LPC (Linear Predictive Coding)-cepstrum coefficients as feature vectors. Finally, we use a competitive learning neural network for speaker verification. The proposed hidden LMS adaptive filter using a neural network reduces noise and enhances features in various noisy conditions. We construct a separate neural network for each speaker, which makes it unnecessary to train the whole network for a new added speaker and makes the system expansion easy. We experimentally prove that the proposed method improves the speaker verification performance.

Text-to-Face Generation Using Multi-Scale Gradients Conditional Generative Adversarial Networks (다중 스케일 그라디언트 조건부 적대적 생성 신경망을 활용한 문장 기반 영상 생성 기법)

  • Bui, Nguyen P.;Le, Duc-Tai;Choo, Hyunseung
    • Proceedings of the Korea Information Processing Society Conference
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    • 한국정보처리학회 2021년도 추계학술발표대회
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    • pp.764-767
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    • 2021
  • While Generative Adversarial Networks (GANs) have seen huge success in image synthesis tasks, synthesizing high-quality images from text descriptions is a challenging problem in computer vision. This paper proposes a method named Text-to-Face Generation Using Multi-Scale Gradients for Conditional Generative Adversarial Networks (T2F-MSGGANs) that combines GANs and a natural language processing model to create human faces has features found in the input text. The proposed method addresses two problems of GANs: model collapse and training instability by investigating how gradients at multiple scales can be used to generate high-resolution images. We show that T2F-MSGGANs converge stably and generate good-quality images.

The Ebb and Flow of Regional Integration Vision in Asia-Pacific: From a Lens of Leaders' Declarations over 30 Years

  • Jeongmeen Suh
    • East Asian Economic Review
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    • 제27권4호
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    • pp.303-325
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    • 2023
  • This paper examines how APEC has transformed itself into an international forum for the vision of regional integration. It aims to quantify the documentation produced by the international organization and provide quantifiable evidence that aligns with prior knowledge rather than relying solely on intuition. For this purpose, I use various text mining techniques to extract multi-dimensional features from the text of APEC Leaders' Declarations from 1993 to 2023. In terms of interest and expectations for APEC as a forum, it is found that members have experienced two major peaks and troughs over the last three decades. It is found that the change point coincides with the Asian financial crisis of 1997 and the tensions between the United States and China since 2017. To explore more various aspects of economic integration in the Asia-Pacific region, this study also considers how consistently APEC has been an international forum for addressing issues, which members are active, and how members have clustered based on their views of APEC.

Helping People with Visual Disability Using AI

  • Naif Al Otaibi;Tariq S Almurayziq
    • International Journal of Computer Science & Network Security
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    • 제24권1호
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    • pp.205-208
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    • 2024
  • Artificial Intelligence (AI) technology has evolved rapidly in recent years and is used in everything from banking to email management to surgery, but without the help of the visible, most of the fun features of the Internet include visual impairment. It benefits people with disabilities. The main purpose of this study is to find ways to help people with visual impairments using AI technology. A visually impaired request is made for the visually impaired. For example, when a message arrives that the program will notify you by voice (reads the sender's name, read the message, and replies to it if necessary), this is a special program installed on your mobile phone. This program uses a customized algorithm developed in Python to convert written text to voice, read text, and convert voice to written text on a message when a visually impaired person wants to respond. Then it sends the response in the form of a text message. Therefore, the research should lead to programs for people with visual impairments. This program makes mobile phones easier and more comfortable to use and makes the daily life easier for visual impairments.

An Image Retrieving Scheme Using Salient Features and Annotation Watermarking

  • Wang, Jenq-Haur;Liu, Chuan-Ming;Syu, Jhih-Siang;Chen, Yen-Lin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권1호
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    • pp.213-231
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    • 2014
  • Existing image search systems allow users to search images by keywords, or by example images through content-based image retrieval (CBIR). On the other hand, users might learn more relevant textual information about an image from its text captions or surrounding contexts within documents or Web pages. Without such contexts, it's difficult to extract semantic description directly from the image content. In this paper, we propose an annotation watermarking system for users to embed text descriptions, and retrieve more relevant textual information from similar images. First, tags associated with an image are converted by two-dimensional code and embedded into the image by discrete wavelet transform (DWT). Next, for images without annotations, similar images can be obtained by CBIR techniques and embedded annotations can be extracted. Specifically, we use global features such as color ratios and dominant sub-image colors for preliminary filtering. Then, local features such as Scale-Invariant Feature Transform (SIFT) descriptors are extracted for similarity matching. This design can achieve good effectiveness with reasonable processing time in practical systems. Our experimental results showed good accuracy in retrieving similar images and extracting relevant tags from similar images.

Text Extraction Algorithm in Natural Image using LoG Operator and Coiflet Wavelet (Coiflet Wavelet과 LoG 연산자를 이용한 자연이미지에서의 텍스트 검출 알고리즘)

  • Shin, Seong;Baek, Young-Hyun;Moon, Sung-Ryong;Shin, Hong-Kyu
    • Proceedings of the IEEK Conference
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    • 대한전자공학회 2005년도 추계종합학술대회
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    • pp.979-982
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    • 2005
  • This paper is to be pre-processing that decides the text recognizability and quality contained in natural image. Differentiated with the existing studies, In this paper, it suggests the application of partially unified color models, Coiflet Wavelet and text extraction algorithm that uses the closed curve edge features of LoG (laplacian of gaussian)operator. The text image included in natural image such as signboard has the same hue, saturation and value, and there is a certain thickness as for their feature. Each color element is restructured into closed area by LoG operator, the 2nd differential operator. The text area is contracted by Hough Transform, logical AND-OR operator of each color model and Minimum-Distance classifier. This paper targets natural image into which text area is added regardless of the size and resolution of the image, and it is confirmed to have more excellent performance than other algorithms with many restrictions.

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The Metaphorical Structure of the Text (텍스트의 은유적 구조)

  • Park, Chan-Bu
    • Journal of English Language & Literature
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    • 제57권5호
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    • pp.871-887
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    • 2011
  • In Lacanian terms, the real, which is a non-representative Ding an sich, is indirectly approachable only in and through language. This 'speaking of the real' is made possible through a restoration of the missing link between one signifier, S1 and another signifier, S2, as is manifested in the Lacanian formula of metaphor. In Freudian terms of textual metaphor, the missing link is restored by substituting a new edition for an old edition of one's historical text of life. This is what this essay means by the metaphorical/dualistic structure of the analytic/literary text. And this is a way of talking about an intertextuality between literature and psychoanalysis in the sense of the 'text as psyche' and the 'psyche as text.' Applying the 'signifying substitution' to the Oedipus complex, the Oedipal child can find a meaning(s), "my erotic indulgement with my Mom is wrong" by metaphorically substituting S2: the Name of the Father for S1: the Desire of the Mother. This meaning leads to the constitution of the human subject and the formation of the incest taboo, one of the most significant distinctive features of the human being as distinguished from the animals. We can see a similar metaphorical structure of S1-S2 taking place in the literary texts such as Macbeth and "Dover Beach": in the course of the stage of life being substituted for the primal scene in the former, and the plain of Tucydides for a bed scene in the latter, respectively.

An Embedded Text Index System for Mass Flash Memory (대용량 플래시 메모리를 위한 임베디드 텍스트 인덱스 시스템)

  • Yun, Sang-Hun;Cho, Haeng-Rae
    • Journal of the Korea Society of Computer and Information
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    • 제14권6호
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    • pp.1-10
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    • 2009
  • Flash memory has the advantages of nonvolatile, low power consumption, light weight, and high endurance. This enables the flash memory to be utilized as a storage of mobile computing device such as PMP(Portable Multimedia Player). Potable device with a mass flash memory can store various multimedia data such as video, audio, or image. Typical index systems for mobile computer are inefficient to search a form of text like lyric or title. In this paper, we propose a new text index system, named EMTEX(Embedded Text Index). EMTEX has the following salient features. First, it uses a compression algorithm for embedded system. Second, if a new insert or delete operation is executed on the base table. EMTEX updates the text index immediately. Third, EMTEX considers the characteristics of flash memory to design insert, delete, and rebuild operations on the text index. Finally, EMTEX is executed as an upper layer of DBMS. Therefore, it is independent of the underlying DBMS. We evaluate the performance of EMTEX. The Experiment results show that EMTEX can outperform th conventional index systems such as Oracle Text and FT3.

ModifiedFAST: A New Optimal Feature Subset Selection Algorithm

  • Nagpal, Arpita;Gaur, Deepti
    • Journal of information and communication convergence engineering
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    • 제13권2호
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    • pp.113-122
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    • 2015
  • Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.

Recognition of Korean Implicit Citation Sentences Using Machine Learning with Lexical Features (어휘 자질 기반 기계 학습을 사용한 한국어 암묵 인용문 인식)

  • Kang, In-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • 제16권8호
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    • pp.5565-5570
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    • 2015
  • Implicit citation sentence recognition is to locate citation sentences which lacks explicit citation markers, from articles' full-text. State-of-the-art approaches exploit word ngrams, clue words, researcher's surnames, mentions of previous methods, and distance relative to nearest explicit citation sentences, etc., reaching over 50% performance. However, most previous works have been conducted on English. As for Korean, a rule-based method using positive/negative clue patterns was reported to attain the performance of 42%, requiring further improvement. This study attempted to learn to recognize implicit citation sentences from Korean literatures' full-text using Korean lexical features. Different lexical feature units such as Eojeol, morpheme, and Eumjeol were evaluated to determine proper lexical features for Korean implicit citation sentence recognition. In addition, lexical features were combined with the position features representing backward/forward proximities to explicit citation sentences, improving the performance up to over 50%.