Refine your search
Collections
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Karpagavalli, S.
- Effect of Trichoderma spp. on Damping-Off Disease of Tomato Caused by Pythium aphanidermatum (Edson) Fitz
Abstract Views :190 |
PDF Views:111
Authors
Affiliations
1 Department of Plant Pathology, Annamalai University, Annamalai Nagar-608 002, IN
1 Department of Plant Pathology, Annamalai University, Annamalai Nagar-608 002, IN
Source
Journal of Biological Control, Vol 9, No 1 (1995), Pagination: 59-60Abstract
Manangement of soil-borne pathogens by using biocontrol agents is an efficient and long term method. The major problem of applying antagonists to soil is their inability to become established in the ecosystem and overcome the resistance of soil microflora to the introduction of new micro organisms (Alexander, 1971).Keywords
Tomato, Damping-Off, Trichoderma harzianum, T. viride.- A Hierarchical Approach in Tamil Phoneme Classification using Support Vector Machine
Abstract Views :293 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, PSGR Krishnammal College for Women, Coimbatore - 641004, Tamil Nadu, IN
2 Department of Computer Science, Bharathiar University, Coimbatore - 641046, Tamil Nadu, IN
1 Department of Computer Science, PSGR Krishnammal College for Women, Coimbatore - 641004, Tamil Nadu, IN
2 Department of Computer Science, Bharathiar University, Coimbatore - 641046, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 35 (2015), Pagination:Abstract
Most of the speech recognition systems are designed based on the sub-word unit phoneme which is the basic sound unit of a language. In the proposed work, a novel hierarchical approach based phoneme classification task has been carried out to reduce time complexity and search space. Hierarchical classification of set of Tamil phonemes has been done in three levels. Phoneme boundaries of the given speech utterance are identified using Spectral Transition Measure (STM) and phonemes are separated. Mel-Frequency Cepstral Coefficients (MFCC) are extracted for each phoneme represented by 9 frames including the contextual frames of corresponding phoneme. In each hierarchical level, different number of models is built using Support Vector Machine (SVM) for classifying each phoneme group/phoneme. It is observed from the results that in hierarchical approach phoneme group recognition rate at level 1 and 2 has greatly improved compared to flat classification model. Complexity of search space is significantly reduced at level 2 and level 3 contrasts to flat phoneme classification model. Hierarchical phoneme classifier can be very well employed in phoneme recognition task which is useful in applications such as spoken term detection, out-ofvocabulary detection, named entity recognition, spoken document retrieval.Keywords
Mel-Frequency Cepstral Coefficients, Spectral Transition Measure- Recognition of Tamil Syllables Using Vowel Onset Points with Production, Perception Based Features
Abstract Views :135 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science, PSGR Krishnammal College for Women, IN
2 Department of Computer Science, Bharathiar University, IN
1 Department of Computer Science, PSGR Krishnammal College for Women, IN
2 Department of Computer Science, Bharathiar University, IN