Goutam Saha

Bio: Goutam Saha is an academic researcher from North Eastern Hill University. The author has contributed to research in topics: Speaker recognition & Gene regulatory network. The author has an hindex of 13, co-authored 143 publications receiving 583 citations. Previous affiliations of Goutam Saha include Indian Institute of Technology Kharagpur & West Bengal University of Technology.

An F-Ratio Based Optimization on Noisy Data for Speaker Recognition Application

Abstract: Automatic Speaker Recognition (ASR) needs a robust acoustic feature for representation of speaker and an efficient modeling scheme to yield high recognition accuracy even at adverse conditions. This paper presents a noise study of an ASR system using Mel-Frequency Cepstral Coefficients (MFCC) and an Artificial Neural Network (ANN) classifier. Optimization in feature space using Fisher's F-Ratio score is done in order to develop reduced speaker model in no noise (only ambient room noise is present) as well as in several noisy conditions. A new ranking scheme is also proposed in order to stabilize the rank of features in various noise levels by taking Arithmetic Mean of the F-Ratio scores obtained from various levels of Signal to Noise Ratio (SNR). The result is presented for a Text-Dependent ASR system with 25 speaker database.

Analysis of Distance Measures for Pre-Quantization before Feature Extraction in Automatic Speaker Recognition

Abstract: The total recognition time as well as the memory requirement in speaker recognition is mainly governed by the number of speakers, the number of frame vectors in the test sequence and the feature dimensionality. The adjacent frame vectors can show similarity in the feature space because of the slow movements of the articulators. Hence efficient frame selection techniques to select non-redundant frames in the preprocessing stage will be very effective in real time application of this recognition system. In pre-quantization (PQ) we select a new sequence of frames Y from the original frames X such that length of Y is less than X. In this paper we propose different distance measure techniques for selecting frames exploiting the redundancies between consecutive frames. The aim is not only to reduce the number of frames for feature extraction but also to maintain the recognition accuracy reasonably high by selecting suitable frames containing speaker specific information. The techniques are evaluated on two different telephone speech databases, POLYCOST and KING.

Improving speaker identification via Singular Value Decomposition based Feature Transformer

Abstract: State-of-the-art Speaker Identification (SI) systems use Gaussian Mixture Models (GMM) for modeling speakerspsila data. Using GMM, a speaker can be identified accurately even from a large number of speakers, when model complexity is large. However, lower ordered speaker model using GMM show poor accuracy as lesser number of Gaussian are involved. In SI context, not much attention have been paid towards improving accuracies for lower order models although they have been used in real-time applications like hierarchical speaker pruning. In this paper, two different approaches have been proposed using Singular Value Decomposition (SVD) based Feature Transformer (FT) for improving accuracies especially for lower ordered speaker models. The results show significant improvements over baseline and have been presented on two widely different public databases comprising of more than 130 speakers.

SD-6LN: Improved Existing IoT Framework by Incorporating SDN Approach

Abstract: The state-of-the-art smart communication system like the Internet of things (IoT) suffers from various limitations like availability, reliability, scalability, interoperability, security, and privacy. Software-defined network (SDN) is an approach that has got many advantages that can solve some of the IoT challenges. IoT and SDN are two categories of networking system, but if they can be merged, then many IoT challenges will be resolved. Practically, it is not possible to discard the existing IoT infrastructure to replace it with any new system. In this paper, the initiative has been undertaken to incorporate the SDN feature in the existing 6LoWPAN-based IoT infrastructure. A new SDN-based 6LoWPAN-IoT infrastructure, namely SD-6LN, has been developed. This has enhanced the availability, reliability, and scalability of resource-constraint networks. The experimental results indicated satisfactory results with respect to round trip time, jitter, and packet drop in this network.

Recent Advances in the Synthesis of Cyclobutanes by Olefin [2+2] Photocycloaddition Reactions

Abstract: The [2 + 2] photocycloaddition is undisputedly the most important and most frequently used photochemical reaction. In this review, it is attempted to cover all recent aspects of [2 + 2] photocycloaddition chemistry with an emphasis on synthetically relevant, regio-, and stereoselective reactions. The review aims to comprehensively discuss relevant work, which was done in the field in the last 20 years (i.e., from 1995 to 2015). Organization of the data follows a subdivision according to mechanism and substrate classes. Cu(I) and PET (photoinduced electron transfer) catalysis are treated separately in sections 2 and 4, whereas the vast majority of photocycloaddition reactions which occur by direct excitation or sensitization are divided within section 3 into individual subsections according to the photochemically excited olefin.

The working brain (an introduction to neuropsychology)

Abstract: CLINICAL NEUROSURGERY Edited by Barnes Wordall. Vol. 18. (Pp. 557; illustrated; £8 25.) Churchill Livingstone: Edinburgh. 1971. CLINICAL NEUROSURGERY Edited by G. T. Tindall. Vol. 19. (Pp. 598; illustrated; £12.) Churchill Livingstone: Edinburgh. 1972. The Congress of Neurosurgeons began in 1951 on the initiative of a group of younger neurosurgeons. In the last 20 years its membership has grown from 69 to over 1,000, but it has retained its original intentions and virility by a constitution which ensured that the office bearers and organizers were always young men. Residents in training are encouraged to join, financial concessions make it possible for them to attend meetings, and these are organized as an educational exercise, by inviting established authorities to give lectures on selected topics, chosen to provide a balanced programme. As a result Clinical Neurosurgery is a valuable volume which all neurosurgeons look forward to each year; it is in quite a different class from the usual conference tome, full of brief and unconnected papers of widely varying quality. As the title suggests Clinical Neurosurgery includes excellent clinical reviews but the two recent volumes include also a section of seminars on fundamental research-in volume 18 on coma and sleep, in volume 19 on basic mechanisms of memory. It is also the custom to invite a senior neurosurgical citizen as guest of honour and his two or three papers afford an opportunity for historical and philosophical reflections as well as an experienced perspective on clinical and experimental work. Add to this the refreshing presidential address, from one of the (angry?) young men of neurosurgery and it will be clear that these volumes really do include something of interest for every neurosurgeon, whatever his own interests or prejudices. It is a relief to be able so warmly to recommend these books, when the question posed by so many other books is whether anyone would really want to read them. The most recent volume has a more consistent theme than former ones, and that is 'head injury'. It includes papers on mechanisms as revealed by animal experiment and by a pathologist who visited the scene of the accident before examining the brains of head injury fatalities. There are chapters on engineering and socio-psychological aspects of accident prevention, as well as down to earth clinical accounts of metabolic disorders, testing for acoustic vestibular 36 damage, and aspects of prognosis. This is a significant contribution to the literature on head injury.