Segmentation,indexing and retrieval of TV broadcast news bulletins using Gaussian mixture models and vector quantization codebooks

In this paper we proposed two-stage segmentation approach for splitting the TV broadcast news bulletins into sequence of news stories and codebooks derived from vector quantization are used for retrieving the segmented stories. At the first stage of segmentation, speaker (news reader) specific characteristics present in initial headlines of news bulletin are used for gross level segmentation. During second stage, errors in the gross level segmentation (first stage) are corrected by exploiting the speaker specific information captured from the individual news stories other than headlines. During headlines the captured speaker specific information is mixed with background music, and hence the segmentation at the first stage may not be accurate. In this work speaker specific information is represented by using mel frequency cepstral coefficients, and captured by Gaussian mixture models (GMMs). The proposed two-stage segmentation method is evaluated on manual segmented broadcast TV news bulletins. From the evaluation results, it is observed that about 93 % of the news stories are correctly segmented, 7 % are missed and 6 % are spurious. For navigating the bulletins, a quick navigation indexing method is developed based on speaker change points. Performance of the proposed two-stage segmentation and quick navigation methods are evaluated using GMM and neural networks models. For retrieving the target news stories from news corpus, sequence of codebook indices derived from vector quantization is explored. Proposed retrieval approach is evaluated using queries of different sizes. Evaluation results indicating that the retrieval accuracy is proportional to size of the query.     

Ultrasonic studies of the binary mixtures of ethyl acetate and cresols—application of Kosower and Dimroth treatments

The ultrasonic velocity (ν) studies were carried out at a frequency of 2 MHz (transducer of x-cut quartz crystal) using ultrasonic pulse echo system (model UX4400-M) on cresols in ethyl acetate at constant temperature of 311 K. The values of internal pressure ( π_i) and molar free volume (V_f) were calculated from measured values of ultrasonic velocity (ν), viscosity (η) and density (ρ). An attempt is made to rationalize the ultrasonic velocity (ν), internal pressure ( π_i) and free volume (V_f) of binary mixtures using Kosower solvent parameter (Z), Dimroth solvent parameter (E_T) and Dielectric constant (). It is found that there is linear correlation between ultrasonic velocity and acidity constant pk⁻¹a, indicating the dependence of acidity. Correlation of Ksower and Dimroth parameters with ultrasonic velocity confirms that solvent polarity is an important factor in the variation of ultrasonic velocity in the present investigation.     

An intelligent character recognizer for Telugu scripts using multiresolution analysis and associative memory

The present work is an attempt to develop a robust character recognizer for Telugu texts. We aim at designing a recognizer, which exploits the inherent characteristics of the Telugu Script. Our proposed method uses wavelet multi-resolution analysis for the purpose extracting features and associative memory model to accomplish the recognition tasks. Our system learns the style and font from the document itself and then it recognizes the remaining characters in the document. The major contribution of the present study can be outlined as follows. It is a robust OCR system for Telugu printed text. It avoids feature extraction process and it exploits the inherent characteristics of the Telugu character by a clever selection of Wavelet Basis function, which extracts the invariant features of the characters. It has a Hopfield-based Dynamic Neural Network for the purpose of learning and recognition. This is important because it overcomes the inherent difficulties of memory limitation and spurious states in the Hopfield Network. The DNN has been demonstrated to be efficient for associative memory recall. However, though it is normally not suitable for image processing application, the multi-resolution analysis reduces the sizes of the images to make the DNN applicable to the present domain. Our experimental results show extremely promising results.     

Efficient attribute-based signature and signcryption realizing expressive access structures

This paper addresses the open problem of designing attribute-based signature (ABS) schemes with constant number of bilinear pairing operations for signature verification or short signatures for more general policies posed by Gagné et al. in Pairing 2012. Designing constant-size ABS for expressive access structures is a challenging task. We design two key-policy ABS schemes with constant-size signature for expressive linear secret-sharing scheme (LSSS)-realizable monotone access structures. Both the schemes utilize only 3 pairing operations in signature verification process. The first scheme is small universe construction, while the second scheme supports large universes of attributes. The signing key is computed according to LSSS-realizable access structure over signer’s attributes, and the message is signed with an attribute set satisfying the access structure. Our ABS schemes provide the existential unforgeability in selective attribute set security model and preserve signer privacy. We also propose a new attribute-based signcryption (ABSC) scheme for LSSS-realizable access structures utilizing only 6 pairings and making the ciphertext size constant. Our scheme is significantly more efficient than existing ABSC schemes. While the secret key (signing key or decryption key) size increases by a factor of number of attributes used in the system, the number of pairing evaluations is reduced to constant. Our protocol achieves (a) ciphertext indistinguishability under adaptive chosen ciphertext attacks assuming the hardness of decisional Bilinear Diffie–Hellman Exponent problem and (b) existential unforgeability under adaptive chosen message attack assuming the hardness of computational Diffie–Hellman Exponent problem. The security proofs are in selective attribute set security model without using any random oracle heuristic. In addition, our ABSC achieves public verifiability of the ciphertext, enabling any party to verify the integrity and validity of the ciphertext.     

Improved consonant–vowel recognition for low bit‐rate coded speech

In this paper, we proposed a method for improving the recognition performance of 145 prominent consonant–vowel (CV) units in Indian languages for low bit‐rate coded speech. Proposed CV recognition method is carried out in two levels to reduce the similarity among a large number of CV classes. In the first level, vowel category of CV unit will be recognized, and in the second level, consonant category will be recognized. At each level of the proposed method, complementary evidences from support vector machine and hidden Markov models are combined to enhance the recognition performance. Effectiveness of the proposed two‐level CV recognition method is demonstrated by performing the recognition of isolated CV units and CV units collected from the Telugu broadcast news database. In this work, vowel onset point (VOP) is used as an anchor point for extracting accurate features from the CV unit. Therefore, a method is proposed for accurate detection of VOP in clean and coded speech. The proposed VOP detection method is based on the spectral energy in 500–2500 Hz frequency band of the speech segments present in the glottal closure region. Speech coders considered in this work are GSM full rate (ETSI 06.10), CELP (FS‐1016), and MELP (TI 2.4 kbps). Significant improvement in CV recognition performance is achieved using the proposed two‐level method compared with the existing methods under both clean and coded conditions. Copyright © 2011 John Wiley & Sons, Ltd.     

Removal of cerium ions from aqueous solution by hydrous ferric oxide--a radiotracer study

Radiotracer technique has been used to study the removal behavior of Ce (III) ions from aqueous solutions by synthesized and well characterized hydrous ferric oxide (HFO). Adsorptive concentration (10(-4)-10(-8) mol dm(-3)), pH (ca 4.0-10.0) and temperature (303-333 K) were examined for assessing optimal conditions for removal of these ions. The uptake of Ce (III) ions, which fitted well for Freundlich and D-R isotherms, increased with increase in the temperature and no significant desorption took place in the studied temperature range. The presence of some anions/cations affected the uptake of metal ion markedly. Irradiation of hydrous ferric oxide and tungsten oxide by using a 11.1×10(9) Bq (Ra-Be) neutron source having a neutron flux of 3.9×10(6) cm(-2) s(-1) with associated γ-dose rate of 1.72 Gy/h did not influence the extent of adsorption of Ce (III) significantly.     

MBNL1-RNA recognition: contributions of MBNL1 sequence and RNA conformation

Muscleblind-like proteins (MBNL) are RNA-binding proteins that bind to the poly(CUG) and poly(CCUG) sequences that are the causative agents of myotonic dystrophy. It has been suggested that as a result of binding to the repeating RNA sequences, MBNL1 is abnormally expressed and translocated, which leads to many of the misregulated events in myotonic dystrophy. In this work, steady-state fluorescence quenching experiments suggest that MBNL1 alters the structure of helical RNA targets upon binding, which may explain the selectivity of MBNL1 for less structured RNA sites. The removal of one pair of zinc fingers greatly impairs the binding affinity of MBNL1, which indicates that the two pairs of zinc fingers might possibly interact with RNA targets cooperatively. Alanine scanning mutagenesis results suggest that the binding energy may be distributed across the protein. Overall, the results presented here suggest that small molecules that stabilize the helical structure of poly(CUG) and poly(CCUG) RNAs will inhibit the formation of complexes with MBNL1.     

Unconstrained Pitch Contour Modification Using Instants of Significant Excitation

This paper proposes a flexible method for pitch contour modification using the instants of significant excitation of the vocal tract system during the production of speech. The instants of significant excitation correspond to the instants of glottal closure (epochs) in the case of voiced speech, and to some random excitations like onset of burst in the case of nonvoiced speech. Instants of significant excitation are computed from the Linear Prediction (LP) residual of speech signals by using the property of average group-delay of minimum phase signals. The modification of pitch contour is achieved by manipulating the LP residual with the help of the knowledge of the instants of significant excitation. The modified residual is used to excite the time-varying filter, whose parameters are derived from the original speech signal. Perceptual quality of the synthesized speech is good, and is without any significant distortion. The proposed method is evaluated using waveforms, spectrograms and listening tests. Listening tests are performed on voice conversion application, where the source speaker’s pitch contour is modified by the proposed method according to the target speaker’s pitch contour. The performance of the proposed method is compared with Linear Prediction Pitch Synchronous Overlap and Add (LP-PSOLA) method using listening tests, for the voice conversion application.