• Title/Summary/Keyword: TDNN bank

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Application of Neural Network Scheme to Performance Enhancement of Rheotruder

  • Kim, Sung-Ho;Lee, Young-Sam;Diaconescu, Bogdana
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.2
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    • pp.114-118
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    • 2005
  • Recently, in order to guarantee the quality of the final product from the production line, several equipments able to examine the polymer ingredients' quality are being used. Rheotruder is one of the equipments manufactured to measure the viscosity of the ingredient that is an important factor for the quality of final product. However, Rheotruder has nonlinear characteristics such as time delay which make systematic analysis difficult. In this paper, in order to enhance the performance of Rheotruder, a new scheme is introduced. It incorporates TDNN (Time Delay Neural Network) bank and Elman network to get a right decision on whether the tested ingredient is good or not. Furthermore, the proposed scheme is verified through real test execution.

A Study on the Diphone Recognition of Korean Connected Words and Eojeol Reconstruction (한국어 연결단어의 이음소 인식과 어절 형성에 관한 연구)

  • ;Jeong, Hong
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.4
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    • pp.46-63
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    • 1995
  • This thesis described an unlimited vocabulary connected speech recognition system using Time Delay Neural Network(TDNN). The recognition unit is the diphone unit which includes the transition section of two phonemes, and the number of diphone unit is 329. The recognition processing of korean connected speech is composed by three part; the feature extraction section of the input speech signal, the diphone recognition processing and post-processing. In the feature extraction section, the extraction of diphone interval in input speech signal is carried and then the feature vectors of 16th filter-bank coefficients are calculated for each frame in the diphone interval. The diphone recognition processing is comprised by the three stage hierachical structure and is carried using 30 Time Delay Neural Networks. particularly, the structure of TDNN is changed so as to increase the recognition rate. The post-processing section, mis-recognized diphone strings are corrected using the probability of phoneme transition and the probability o phoneme confusion and then the eojeols (Korean word or phrase) are formed by combining the recognized diphones.

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