http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Vineet Pandey (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Speech Recognition using Machine Learning
Vineet Vashisht,Aditya Kumar Pandey,Satya Prakash Yadav 대한전자공학회 2021 IEIE Transactions on Smart Processing & Computing Vol.10 No.3
Speech recognition is one of the fastest-growing engineering technologies. It has several applications in different areas, and provides many potential benefits. A lot of people are unable to communicate due to language barriers. We aim to reduce this barrier via our project, which was designed and developed to achieve systems in particular cases to provide significant help so people can share information by operating a computer using voice input. This project keeps that factor in mind, and an effort is made to ensure our project is able to recognize speech and convert input audio into text; it also enables a user to perform file operations like Save, Open, or Exit from voice-only input. We design a system that can recognize the human voice as well as audio clips, and translate between English and Hindi. The output is in text form, and we provide options to convert audio from one language to the other. Going forward, we expect to add functionality that provides dictionary meanings for Hindi and English words. Neural machine translation is the primary algorithm used in the industry to perform machine translation. Two recurrent neural networks used in tandem to construct an encoder-decoder structure are the architecture behind neural machine translation. This work on speech recognition starts with an introduction to the technology and the applications used in different sectors. Part of the report is based on software developments in speech recognition.
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Analysis and Comparison of Tree Indexing Structures in Flash Memory Models
조승범(SeungBum Jo),Vineet Pandey,Srinivasa Rao Satti 한국정보과학회 2012 정보과학회논문지 : 시스템 및 이론 Vol.39 No.1
현재 플래시 메모리 장치들은 다양한 곳에 이용되고 있으며 기존의 외부 저장 장치들을 빠르게 대체하고 있다. 플래시 메모리 하에서 자료들을 효과적으로 저장하기 위해서는 이에 적합한 파일 시스템과 인덱스 구조를 사용할 필요가 있으며 이에 대해 많은 연구가 이루어져 왔다. 하지만 플래시 메모리 모델에 대한 이론적인 기반의 부족으로 인해 이 구조들의 성능을 서로 비교하기 힘들었으며 기존의 외부 메모리 모델은 플래시 메모리의 특징들을 반영하는 데 있어 어려움이 있어 왔다. 이 논문에서 우리는 플래시 메모리에 적합하게 제안 된 다양한 인덱스 구조들에 대해 알아보고 최근에 제안된 플래시 메모리 모델을 사용하여 이들의 성능을 분석한다. Flash memory devices are becoming ubiquitous and indispensable storage devices, partly even replacing the traditional hard-disks. To store data efficiently on these devices, it is necessary to adapt the existing file systems and indexing structures to work well on the flash memory, and a significant amount of research in this field has been devoted to designing such structures. But it is hard to compare these structures owing to the lack of any theoretical memory models for flash memory and since the existing external memory models fail to capture the full potential of flash-based storage devices. In this paper we study various index structures that have been shown to perform well on flash memory, and analyze them in the recently proposed flash memory models.
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AN EFFICIENT AND STABLE ALGORITHM FOR NUMERICAL EVALUATION OF HANKEL TRANSFORMS
Singh, Om P.,Singh, Vineet K.,Pandey, Rajesh K. The Korean Society for Computational and Applied M 2010 Journal of applied mathematics & informatics Vol.28 No.5
Recently, a number of algorithms have been proposed for numerical evaluation of Hankel transforms as these transforms arise naturally in many areas of science and technology. All these algorithms depend on separating the integrand $rf(r)J_{\upsilon}(pr)$ into two components; the slowly varying component rf(r) and the rapidly oscillating component $J_{\upsilon}(pr)$. Then the slowly varying component rf(r) is expanded either into a Fourier Bessel series or various wavelet series using different orthonormal bases like Haar wavelets, rationalized Haar wavelets, linear Legendre multiwavelets, Legendre wavelets and truncating the series at an optimal level; or approximating rf(r) by a quadratic over the subinterval using the Filon quadrature philosophy. The purpose of this communication is to take a different approach and replace rapidly oscillating component $J_{\upsilon}(pr)$ in the integrand by its Bernstein series approximation, thus avoiding the complexity of evaluating integrals involving Bessel functions. This leads to a very simple efficient and stable algorithm for numerical evaluation of Hankel transform.
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