Some Advances in Nonlinear Speech Modeling Using Modulations, Fractals, and Chaos

In this paper we briefly summarize our on-going work on modeling nonlinear structures in speech signals, caused by modulation and turbulence phenomena, using the theories of modulation, fractals, and chaos as well as suitable nonlinear signal analysis methods. Further, we focus on two advances: i) AM-FM modeling of fricative sounds with random modulation signals of the 1/f-noise type and ii) improved methods for speech analysis and prediction on reconstructed multidimensional attractors. 1

A Mathematical Morphology Approach to Cell Shape Analysis

This contribution aims to apply mathematical morphology operators to quantify the shape of round-objects which present irregularities from an ideal circular pattern. More specifically we illustrate, on the one hand, the application of morphological granulometries for size/shape multi-scale description and on the other hand, the radial/angular decompo- sitions using skeletons in polar-logarithmic representation. We discuss also the aspects related to the properties of invariance of these tools, which is important to describe cell shapes acquired under different magnifications, orientations, etc

Audio-assisted movie dialogue detection

An audio-assisted system is investigated that detects if a movie scene is a dialogue or not. The system is based on actor indicator functions. That is, functions which define if an actor speaks at a certain time instant. In particular, the cross-correlation and the magnitude of the corresponding the cross-power spectral density of a pair of indicator functions are input to various classifiers, such as voted perceptions, radial basis function networks, random trees, and support vector machines for dialogue/non-dialogue detection. To boost classifier efficiency AdaBoost is also exploited. The aforementioned classifiers are trained using ground truth indicator functions determined by human annotators for 41 dialogue and another 20 non-dialogue audio instances. For testing, actual indicator functions are derived by applying audio activity detection and actor clustering to audio recordings. 23 instances are randomly chosen among the aforementioned 41 dialogue instances, 17 of which correspond to dialogue scenes and 6 to non-dialogue ones. Accuracy ranging between 0.739 and 0.826 is reported. © 2008 IEEE

The Lagoon at Caroline/Millennium Atoll, Republic of Kiribati: Natural History of a Nearly Pristine Ecosystem

A series of surveys were carried out to characterize the physical and biological parameters of the Millennium Atoll lagoon during a research expedition in April of 2009. Millennium is a remote coral atoll in the Central Pacific belonging to the Republic of Kiribati, and a member of the Southern Line Islands chain. The atoll is among the few remaining coral reef ecosystems that are relatively pristine. The lagoon is highly enclosed, and was characterized by reticulate patch and line reefs throughout the center of the lagoon as well as perimeter reefs around the rim of the atoll. The depth reached a maximum of 33.3 m in the central region of the lagoon, and averaged between 8.8 and 13.7 m in most of the pools. The deepest areas were found to harbor large platforms of Favia matthaii, which presumably provided a base upon which the dominant corals (Acropora spp.) grew to form the reticulate reef structure. The benthic algal communities consisted mainly of crustose coralline algae (CCA), microfilamentous turf algae and isolated patches of Halimeda spp. and Caulerpa spp. Fish species richness in the lagoon was half of that observed on the adjacent fore reef. The lagoon is likely an important nursery habitat for a number of important fisheries species including the blacktip reef shark and Napoleon wrasse, which are heavily exploited elsewhere around the world but were common in the lagoon at Millennium. The lagoon also supports an abundance of giant clams (Tridacna maxima). Millennium lagoon provides an excellent reference of a relatively undisturbed coral atoll. As with most coral reefs around the world, the lagoon communities of Millennium may be threatened by climate change and associated warming, acidification and sea level rise, as well as sporadic local resource exploitation which is difficult to monitor and enforce because of the atoll's remote location. While the remote nature of Millennium has allowed it to remain one of the few nearly pristine coral reef ecosystems in the world, it is imperative that this ecosystem receives protection so that it may survive for future generations

Pattern Spectra from Different Component Trees for Estimating Soil Size Distribution

We study the pattern spectra in context of soil structure analysis. Good soil structure is vital for sustainable crop growth. Accurate and fast measuring methods can contribute greatly to soil management decisions. However, the current in-field approaches contain a degree of subjectivity, while obtaining quantifiable results through laboratory techniques typically involves sieving the soil which is labour- and time-intensive. We aim to replace this physical sieving process through image analysis, and investigate the effectiveness of pattern spectra to capture the size distribution of the soil aggregates. We calculate the pattern spectra from partitioning hierarchies in addition to the traditional max-tree. The study is posed as an image retrieval problem, and confirms the ability of pattern spectra and suitability of different partitioning trees to re-identify soil samples in different arrangements and scales

A time-frequency analysis approach for condition monitoring of a wind turbine gearbox under varying load conditions

This paper deals with the condition monitoring of wind turbine gearboxes under varying operating conditions. Generally, gearbox systems include nonlinearities so a simplified nonlinear gear model is developed, on which the time–frequency analysis method proposed is first applied for the easiest understanding of the challenges faced. The effect of varying loads is examined in the simulations and later on in real wind turbine gearbox experimental data. The Empirical Mode Decomposition (EMD) method is used to decompose the vibration signals into meaningful signal components associated with specific frequency bands of the signal. The mode mixing problem of the EMD is examined in the simulation part and the results in that part of the paper suggest that further research might be of interest in condition monitoring terms. For the amplitude–frequency demodulation of the signal components produced, the Hilbert Transform (HT) is used as a standard method. In addition, the Teager–Kaiser energy operator (TKEO), combined with an energy separation algorithm, is a recent alternative method, the performance of which is tested in the paper too. The results show that the TKEO approach is a promising alternative to the HT, since it can improve the estimation of the instantaneous spectral characteristics of the vibration data under certain conditions