Face verification in the presence of age progression is an important problem that has not been widely addressed. Despite appearance changes for same person due to aging, they are more similar compared to facial images from different individuals. Hence, we design common and adapted vocabularies, where common vocabulary describes contents of general population and adapted vocabulary represents specific characteristics of one of image facial pairs. And the other image is characterized with a concatenation histogram of common and adapted visual words counts, termed as “age-invariant distinctive representation”. The representation describes whether the image content is best modeled by the common vocabulary or the corresponding adapted vocabulary, which is further used to accomplish the face verification. The proposed approach is tested on the FGnet dataset and a collection of real-world facial images from identification card. The experimental results demonstrate the effectiveness of the proposed method for verification of identity at a modest computational cost.

Almost sure convergence coding theorems of one-shot and multi-shot Tunstall codes are proved for stationary memoryless sources. Coding theorem of one-shot Tunstall code is proved in the case that the leaf count of Tunstall tree increases. On the other hand, coding theorem is proved for multi-shot Tunstall code with increasing parsing count, under the assumption that the Tunstall tree grows as the parsing proceeds. In this result, it is clarified that the theorem for the one-shot Tunstall code is not a corollary of the theorem for the multi-shot Tunstall code. In the case of the multi-shot Tunstall code, it can be regarded that the coding theorem is proved for the sequential algorithm such that parsing and coding are processed repeatedly. Cartesian concatenation of trees and geometric mean of the leaf counts of trees are newly introduced, which play crucial roles in the analyses of multi-shot Tunstall code.

Corpus-based concatenative speech synthesis has been widely investigated and deployed in recent years since it provides a highly natural synthesized speech quality. The amount of computation required in the run time, however, can often be quite large. In this paper, we propose early stopping schemes for Viterbi beam search in the unit selection, with which we can stop early in the local Viterbi minimization for each unit as well as in the exploration of candidate units for a given target. It takes advantage of the fact that the space of the acoustic parameters of the database units is fixed and certain lower bounds of the concatenation costs can be precomputed. The proposed method for early stopping is admissible in that it does not change the result of the Viterbi beam search. Experiments using probability-based concatenation costs as well as distance-based costs show that the proposed methods of admissible stopping effectively reduce the amount of computation required in the Viterbi beam search while keeping its result unchanged. Furthermore, the reduction effect of computation turned out to be much larger if the available lower bound for concatenation costs is tighter.

The measure of the goodness, or inversely the cost, of concatenating synthesis units plays an important role in concatenative speech synthesis. In this paper, we present a probabilistic approach to concatenation modeling in which the goodness of concatenation is measured by the conditional probability of observing the spectral shape of the current candidate unit given the previous unit and the current phonetic context. This conditional probability is modeled by a conditional Gaussian density whose mean vector has a form of linear transform of the past spectral shape. Decision tree-based parameter tying is performed to achieve robust training that balances between model complexity and the amount of training data available. The concatenation models are implemented for a corpus-based speech synthesizer, and the effectiveness of the proposed method was confirmed by an objective evaluation as well as a subjective listening test. We also demonstrate that the proposed method generalizes some popular conventional methods in that those methods can be derived as the special cases of the proposed method.

Using several high rate recursive convolutional codes as the basic element and the trace criteria as the designing principle, a new kind of recursive space-time trellis code with more flexible and higher data rate is presented for the serially concatenated space-time code. When 2b-ary modulation and N transmit antennas are used, the data rate of the new code can be arranged from b bps/Hz to Nb-1bps/Hz by modifying the number of recursive convolutional codes and the data rate of each code.

This paper describes the special demands of conversational speech in the context of corpus-based speech synthesis. The author proposed the CHATR system of prosody-based unit-selection for concatenative waveform synthesis seven years ago, and now extends this work to incorporate the results of an analysis of five-years of recordings of spontaneous conversational speeech in a wide range of actual daily-life situations. The paper proposes that the expresion of affect (often translated as 'kansei' in Japanese) is the main factor differentiating laboratory speech from real-world conversational speech, and presents a framework for the specification of affect through differences in speaking style and voice quality. Having an enormous corpus of speech samples available for concatenation allows the selection of complete phrase-sized utterance segments, and changes the focus of unit selection from segmental or phonetic continuity to one of prosodic and discoursal appropriateness instead. Samples of the resulting large-corpus-based synthesis can be heard at http://feast.his.atr.jp/AESOP.

In this letter, we investigate serially concatenated space-time codes (SC-STs) applying iterative decoding topologies in wideband code division multiple access (WCDMA) communication systems. In the decoding algorithm, an iterative (turbo) process is used, where a priori probability (APP) is exchanged between the symbol-by-symbol space-time (ST) decoder and the bit-by-bit convolutional decoder. The experimental results show that in a Rayleigh fading channel environment the serially concatenated interleaved space-time coding systems show significant error correction capability, and based on the applied system configurations, the nonrecursive ST code outperforms the recursive ST code.

The effects of hybrid concatenated space-time (HC-ST) codes applying iterative a posteriori probability (APP) decoding are investigated. The bit error rate (BER) and frame error rate (FER) performance of the iterative decoded hybrid Tarokh, Seshadri, Calderbank space-time (TSC ST) coded system under flat Rayleigh fading is analyzed. At the FER 10-2 level the results show that the serially concatenated space-time (SC-ST) codes provide a coding gain of 3 dB compared to the TSC ST codes, where an additional coding gain of 1 dB beyond the SC-ST code performance can be obtained applying the HC-ST coding topology.

Recently two interesting conjectures on the linear complexity of binary complementary sequences of length 2nN0 were given by Karkkainen and Leppanen when those sequences are considered as periodic sequences with period 2nN0, where those sequences are constructed by successive concatenations or successive interleavings from a pair of kernel complementary sequences of length N0. Their conjectures were derived from numerical examples and suggest that those sequences have very large linear complexities. In this paper we give the exact formula of characteristic polynomials for those complementary sequences and show that their conjectures are true.