Automatic summarization of voicemail messages using lexical and prosodic features

This article presents trainable methods for extracting principal content words from voicemail messages. The short text summaries generated are suitable for mobile messaging applications. The system uses a set of classifiers to identify the summary words with each word described by a vector of lexical and prosodic features. We use an ROC-based algorithm, Parcel, to select input features (and classifiers). We have performed a series of objective and subjective evaluations using unseen data from two different speech recognition systems as well as human transcriptions of voicemail speech

ML estimation of a stochastic linear system with the EM algorithm and its application to speech recognition

Summarization: A nontraditional approach to the problem of estimating the parameters of a stochastic linear system is presented. The method is based on the expectation-maximization algorithm and can be considered as the continuous analog of the Baum-Welch estimation algorithm for hidden Markov models. The algorithm is used for training the parameters of a dynamical system model that is proposed for better representing the spectral dynamics of speech for recognition. It is assumed that the observed feature vectors of a phone segment are the output of a stochastic linear dynamical system, and it is shown how the evolution of the dynamics as a function of the segment length can be modeled using alternative assumptions. A phoneme classification task using the TIMIT database demonstrates that the approach is the first effective use of an explicit model for statistical dependence between frames of speechΠαρουσιάστηκε στο: IEEE Transactions on Speech and Audio Processin

Fast algorithms for phone classification and recognition using segment-based models

Summarization: Methods for reducing the computation requirements of joint segmentation and recognition of phones using the stochastic segment model are presented. The approach uses a fast segment classification method that reduces computation by a factor of two to four, depending on the confidence of choosing the most probable model. A split-and-merge segmentation algorithm is proposed as an alternative to the typical dynamic programming solution of the segmentation and recognition problem, with computation savings increasing proportionally with model complexity. Although the current recognizer uses context-independent phone models, the results reported for the TIMIT database for speaker-independent joint segmentation and recognition are comparable to those of systems that use context informationPresented on: IEEE Transactions on Signal Processin

Crystallography, vibrational, electronic and optical analysis of 4-Bromo-2-(2,5-dichloro-phenylimino)-phenol

This work reports synthesis and characterization of a novel compound, 4-Bromo-2-(2,5-dichloro-phenylimino)-phenol (BDP). The crystal structure of this Schiff base is determined and compared with DFT calculations. Density functional theory (DFT) and time dependent density functional theory (TD-DFT) is applied to study the optical, electronic properties, vibrational frequencies and optimized structure of 4-Bromo-2-(2,5-dichloro-phenylimino)-phenol by B3LYP, M06–2X, and ab initio (HF) methods and 6–311++G (d,p) basis set. The geometry and electronic properties, thermodynamic functions and atomic charges of the title compound are reported too. Finally, the calculated normal mode vibrational frequencies provide thermodynamic properties through the principle of statistical mechanics. A natural bond orbital (NBO) analysis was carried out to explain the charge transfer or delocalization of charge due to intra-molecular interactions. © 2018 Elsevier B.V