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9th International Workshop on Semantic Evaluation, SemEval 2015

作者： Sundaram, Mahalakshmi Shanmuga Madasamy, Anand Kumar Padannayil, Soman Kotti Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9781941643402

We explore using recursive autoencoders for SemEval 2015 Task 1: Paraphrase and Semantic Similarity in Twitter. Our paraphrase detection system makes use of phrase-structure parse tree embeddings that are then provided as input to a conventional supervised classification model. We achieve an F1 score of 0.45 on paraphrase identification and a Pearson correlation of 0.303 on computing semantic similarity. © 2015 Association for computational Linguistics

关键词： Semantics

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A computational framework for Tamil document classification using Random Kitchen Sink

A computational framework for Tamil document classification ...

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International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015

作者： Sanjanasri, J.P. Anand Kumar, M. Center for Excellence in Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham India

ISBN: (纸本)9781479987917

Along the prompt growth in World Wide Web, the availability and accessibility of regional language contents such as e-books, web pages, e-mails, and digital repositories has grown exponentially. As a result, the automatic document classification has become the hotspot for fetching information among the millions of web documents. The idea of classifying the text, forms the baseline for many NLP applications such as information extraction, query response, information summarization, etc. The main objective of this paper is to develop an computational framework for supervised Tamil document classification task. This paper highlights the performance of Random Kitchen Sink, a randomization algorithm, in Grand Unified Regularized Least Squares (GURLS), a Machine Learning Library, is proven to be comparably better than the conventional kernel based classifier in terms of accuracy. Henceforth, we claim that Random Kitchen Sink can be an effective alternative to the kernels for a classifier. © 2015 IEEE.

关键词： Support vector machines

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Preliminary Studies towards Improving the Isolated Digit Recognition Performance of Dysarthric Speech by Prosodic Analysis

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Procedia Computer Science 2015年 58卷 395-400页

作者： A. Vishakh D. Govind D. Pravena Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham (University) Coimbatore Tamilnadu

The objective of the present work is to improve the digit recognition performance of speech signals affected with dysarthria. The paper presents preliminary studies performed on universal access dysarthric speech recognition (UADSR) database. The works presented in the paper are organized into three stages. Firstly, the degradation in the digit recognition performance is demonstrated by testing the dysarthric digits with the acoustic models built using the digit samples spoken by controlled speakers. Secondly, the prosodic analysis is performed on the dysarthric isolated digits that are available in the database. Finally, the prosodic parameters of the dysarthric speech is manipulated to match with the normal speech which is used to build the acoustic models. Based on the experiments conducted, the manipulation of duration parameters using the state of the art time-domain pitch synchronous overlap add (TD-PSOLA) method observed to be significantly improving the recognition rates in contrast to other prosodic parameters. The improvement in the word recognition rates are also found to be in accordance with the intelligibility of the dysarthric speakers and hence proves the significance of using customized prosodic scaling factors according to the intelligibility levels of each of the subjects.

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A Robust Algorithm for Speech Polarity Detection Using Epochs and Hilbert Phase Information

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Procedia Computer Science 2015年 58卷 524-529页

作者： D. Govind P.M. Hisham D. Pravena Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham (University) Coimbatore Tamilnadu

The aim of the proposed work presented in this paper is to determine the speech polarity using the knowledge of epochs and the cosine phase information derived from the complex analytic representation of original speech signal. The work presented in this paper is motivated by the observation of variations in the cosine phase of speech around the Hilbert envelope (HE) peaks according to the polarity changes. As the HE peaks represent approximate epochs location, the phase analysis is performed by using algorithms which provide better resolution and accuracy of estimated epochs in the present work. In the present work, accurate epochs locations are initially estimated and significant HE peaks are only selected from the near vicinity of the epochs location for phase analysis. The cosine phase of the speech signal is then computed as the ratio of signal to the HE of speech. The trend in the cosine phase around the selected significant HE peaks are observed to be varying according to the speech polarity. The proposed polarity detection algorithm shows better results as compared with the state of the residual skewness based speech polarity detection (RESKEW) method. Thus, the improvement in the polarity detection rates confirms significant polarity information present in the excitation source characteristics around epochs location in speech. The polarity detection rates are also found to be less affected for different levels of noise addition which indicates the effectiveness of the approach against noises. Also, based on the analysis of mean execution time, the proposed polarity detection algorithm is confirmed to be 10 times faster than the RESKEW algorithm.

关键词： Speech polarity detection cosine phase Hilbert envelope

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Study of multirate systems and filter banks using GNU Radio

Study of multirate systems and filter banks using GNU Radio

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International Conference on Communication and Signal Processing, ICCP 2015

作者： Kiran, S. Lekshmi Mol, Parvathy G. Hisham, P.M. Gandhiraj, R. Soman, K.P. Center of Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Amritanagar Coimbatore Tamilnadu641112 India Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Coimbatore Tamiinadu641112 India

ISBN: (纸本)9781479980819

Multirate digital signal processing finds application in various fields like speech processing, image processing and compression. A proper study of this subject is fundamental to incorporating an efficient design of these systems. A good theoretical explanation in this area is readily available at large numbers. But it is quite unfortunate that the present education system does not emphasize a proper visualization of the theoretical concepts. The significance of GNU Radio, which provides various signal processing blocks, is worth noticing since it can be used by a learner to design a flow graph and analyze its response. In this paper, we have implemented the perfect reconstruction filter using the concept of Quadrature mirror filter (QMF) bank in GNU Radio. Some basic concepts like aliasing and filter design have also been analyzed using GNU Radio. We appreciate the role played by GNU Radio since it is an easy-to-use software and also provides an excellant platform in analyzing a system. © 2015 IEEE.

关键词： Digital signal processing

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Cross-Lingual Preposition Disambiguation for Machine Translation

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Procedia Computer Science 2015年 54卷 291-300页

作者： M. Anand Kumar S. Rajendran K.P. Soman Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore 641 112 India

This paper presents a supervised prepositional ambiguity resolution method for machine translation models in which the target language is Tamil and source language is English. We restrict our transfer ambiguity resolution problem with few prepositions only. This resolution method is based on supervised models which exploit collocation occurrences and linguistic information as features. This attempt will rectify the challenges in handling prepositions in English to Tamil automatic translation system. The preliminary results obtained from the evaluation shows that the proposed method is suitable for preposition resolution problem.

关键词： Feature extraction Machine learning Machine translation Natural language processing Preposition disambiguation.

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A Contextual Investigation for Variation in Weather Parameter for Coimbatore District

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Procedia Computer Science 2015年 58卷 507-515页

作者： M. Kokila P. Geetha K.P. Soman Remote Sensing and Wireless Sensor Networks Center for Excellence in Computational Engineering and NetworkingAmrita Vishwa VidyapeethamCoimbatore. Hod Center for Excellence in Computational Netwroking and EngineeringAmrita Vishwa VidyapeethamCoimbatore.

Weather parameters are critical parameter which is to be considered for understanding atmospheric variation. The aim of this paper is to see how the parameter values fluctuates for three decades. Three decade information is isolated into two and K-means machine learning calculation is utilized for bunching the divided data. Then how the information focuses are conveyed around the centroid of every sectioned data group is confirmed. At long last the group for initial one and half decade is compared with the second one and half decade to know how the information focuses are strayed in dynamic year. This gathering is validated with silhouette value.

关键词： Machine learning K-means Silhouette value

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Corrigendum to "Interactive effect of beta-adrenergic stimulation and mechanical stretch on low-frequency oscillations of ventricular action potential duration in humans" [J. Mol. Cell. Cardiol. 97 (2016) 93-105]

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Journal of molecular and cellular cardiology 2018年 121卷 305页

作者： Esther Pueyo Michele Orini José F Rodríguez Peter Taggart Biomedical Signal Interpretation and Computational Simulation (BSICoS) group Aragón Institute of Engineering Research IIS Aragón University of Zaragoza Edificio I+D+i C/ Mariano Esquillor s/n 50018 Zaragoza Spain Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN) Instituto de Salud Carlos III C/ Monforte de Lemos 3-5 pabellón 11 planta 0 28029 Madrid Spain. Electronic address: epueyo@unizar.es. Institute of Cardiovascular Science University College London Gower Street WC1E 6BT London United Kingdom. LaBS Department of Chemistry Materials and Chemical Engineering 'Giulio Nata' Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano Italy.

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Improved Method for Epoch Estimation in Telephonic Speech Signals Using Zero Frequency Filtering

Improved Method for Epoch Estimation in Telephonic Speech Si...

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IEEE International Conference on Signal and Image Processing Applications

作者： D. Govind R. Vishnu D. Pravena Center for Computational Engineering and Networking Amrita Vishwa Vidyapeetham (University) Coimbatore Tamilnadu-641112

ISBN: (纸本)9781479989973

Epochs are the locations correspond to glottal closure instants for voiced speech segments and onset of bursts or frication in unvoiced segments. In the recent years, the zero frequency filtering (ZFF) based epoch estimation has received a growing attention for clean or studio speech signals. The ZFF based epoch estimation exploits the impulse like excitation characteristics at the zero frequency (DC) region in speech. As the lower frequency regions in telephonic speech are significantly attenuated, ZFF approach gives degraded epoch estimation performance. Therefore, the objective of the present work is to propose refinements to the existing ZFF based epoch estimation algorithm for improved epoch estimation in telephonic speech. The strength of the impulses at the zero frequency region are enhanced by computing the Hilbert envelope (HE) of the speech which in turn improve the epoch estimation performance. The resonators located at the approximate Fo locations of the short term blocks of conventional zero frequency filtered signal, are also found to improve the epoch estimation performance in telephonic speech. The performance of the refined ZFF method is evaluated on 3 speaker voices (JMK, SLT and BDL) of CMU Arctic database having simultaneous speech and EGG recordings. The telephonic version of CMU Arctic database is simulated using tools provided by the international telecommunication union (ITU).

关键词： ZFF ITU JMK EPOCH International Telecommunication Union Intensive Care Units zero frequency Speech Pulses

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Recursive Variational Mode Decomposition Algorithm for Real Time Power Signal Decomposition

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Procedia Technology 2015年 21卷 540-546页

作者： Soman K.P. Prabaharan Poornachandran Athira S. Harikumar K. Center for excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Amrita Centre for Cyber Security systems and Networks Amrita Vishwa Vidyapeetham

Conventional methods of signal decomposition are observed to fail in power system applications and computationally intensive algorithms like EMD, VMD, EWT are found to give better performance. The heavy computations associated with them restricts their use in real time applications and stream processing. This paper presents a recursive block processing technique for real time signal decomposition. The use of recursive FFT and the clever initializations of the center frequencies in the existing VMD algorithm helps in reducing the computational complexity and hence speeds up the process. This low complexity algorithm was tested on synthetically generated power signals and the results were observed to be consistent with the existing VMD algorithm.

关键词： Recursive FFT VMD computational complexity power signal decomposition.

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