Multivariate analyses are well known and widely used to identify and understand structures of ecological communities. The ade4 package for the R statistical environment proposes a great number of multivariate methods. Its implementation follows the tradition of the French school of ”Analyse des Données ” and is based on the use of the duality diagram. We present the theory of the duality diagram and discuss its implementation in ade4. Classes and main functions are presented. An example is given to illustrate the ade4 philosophy.

After decades of research, automatic speech processing has become more and more viable in recent years. Audio-video speech recognition has been shown to improve the recognition rate in noise-degraded environments. However, which audio and video speech parameters to choose for an optimal system and how they are related is still an open research issue. Here we present a number of statistical analyses that aim at increasing our understanding of such audio-video relationships. In particular, we look at the canonical correlation analysis and the coinertia analysis which investigate the relationship of linear combinations of parameters. The analyses are performed on Australian English as an example.

Multimodality is a key issue in robust humancomputer interaction. The joint use of audio and video speech variables has been shown to improve the performance of automatic speech recognition (ASR) systems. However, robust methods in particular for the real-time extraction of video speech features are still an open research area. This paper addresses the robustness issue of audio-video (AV) ASR systems by exploring a real-time 3D lip tracking algorithm based on stereo vision and by investigating how learned statistical relationships between the sets of audio and video speech variables can be employed in AV ASR systems. The 3D lip tracking algorithm combines colour information from each cameras ’ images with knowledge about the structure of the mouth region for different degrees of mouth openness. By using a calibrated stereo camera system, 3D coordinates of facial features can be recovered, so that the visual speech variable measurements become independent from the head pose. Multivariate statistical analyses enable the analysis of relationships between sets of variables. Co-inertia analysis is a relatively new method and has not yet been widely used in AVSP research. Its advantage is its superior numerical stability compared to other multivariate methods in the case of small sample size. Initial results are presented, which show how 3D video speech information and learned statistical relationships between audio and video speech variables can improve the performance of AV ASR systems. 1.

We investigate the use of audio-visual speech synchrony measure in the framework of identity verification based on talking faces. Two synchrony measures based on Canonical Correlation Analysis and Co-Inertia Analysis respectively are introduced and their performances are evaluated on the specific task of detecting synchronized and notsynchronized audio-visual speech sequences. The notion of higheffort impostor attacks is also introduced as a dangerous threat for current biometric system based on speaker verification and face recognition. A novel biometric modality based on synchrony measures is introduced in order to improve the overall performance of identity verification, and more specifically its robustness to replay attacks. Index Terms — Identification of persons, Speech processing, Video signal processing

We propose a new approach to the multivariate analysis of data sets with known sampling site spatial positions. A between-sites neighbouring relationship must be derived from site positions and this relationship is introduced into the multivariate analyses through neighbouring weights (number of neighbours at each site) and through the matrix of the neighbouring graph. Eigenvector analysis methods (e.g., principal component analysis, correspondence analysis) can then be used to detect total, local and global structures. The introduction of the D-centring (centring with respect to the neighbouring weights) allows us to write a total variance decomposition into local and global components, and to propose a unified view of several methods. After a brief review of the matrix approach to this problem, we present the results obtained on both simulated and real data sets, showing how spatial structure can be detected and analysed. Freely available computer programs to perform computations and graphical displays are proposed.

Speech is a means of communication that is intrinsically bimodal: the audio signal originates from the dynamics of the articulators. This paper reviews recent works in the field of audiovisual speech and more specifically on techniques developed to measure the level of correspondence between audio and visual speech. It overviews the most common audio and visual speech front-end processing, transformations performed on audio, visual or joint audiovisual feature spaces and the actual measure of correspondence between audio and visual speech. Finally, applications of this specific task are described. 1

Abstract. Natural speech is produced by the vocal organs of a particular talker. The acoustic features of the speech signal must therefore be correlated with the movements of the articulators (lips, jaw, tongue, velum,...). For instance, hearing impaired people (and not only them) improve their understanding of speech by lip reading. This chapter is an overview of audiovisual speech processing with emphasis on some experiments concerning recognition, speaker verification, indexing and corpus based synthesis from tongue and lips movements. 1

enes were analyzed by PCR, and the genetic background was determined by means of amplified fragment length polymorphism (AFLP) analysis. The isolates were relatively evenly distributed among the four agr groups, with 61 strains belonging to agr group I, 49 belonging to group II, 43 belonging to group III, and 45 belonging to group IV. Principal coordinate analysis performed on the AFLP distance matrix divided the 198 strains into three main phylogenetic groups, AF1 corresponding to strains of agr group IV, AF2 corresponding to strains of agr groups I and II, and AF3 corresponding to strains of agr group III. This indicated that the agr type was linked to the genetic background. A relationship between genetic background, agr group, and disease type was observed for several toxinmediated diseases: for instance, agr group IV strains were associated with generalized exfoliative syndromes, and phylogenetic group AF1 strains with bullous impetigo. Among the suppurative infections, e

Research article Cross-platform comparison and visualisation of gene expression data using co-inertia analysis

Relationships between soil characteristics, various forms of soil organic matter, microbial biomass and the structure of phytoparasitic nematode populations were investigated in six fallow fields aged from 1 to 26 years in the West African Savanna (WAS) belt in southern Senegal. Soil sampling was performed along two transects in each field. Herbaceous biomass and soil physical, chemical and biological characteristics were studied with principal component analysis (PCA) and the relationships between the parameters were extracted with co-inertia analysis. Soil properties (mainly calcium, magnesium and total carbon contents, and cation exchange capacity) slightly improved in the upper soil layer (0--5 cm) during the succession of vegetation. In constrast, in the 0--10 cm soil layer, microbial biomass and total soil organic carbon content showed no clear pattern of change over time, while highest charcoal stocks were found in older fallows where bush fires are frequent. In the 0--40 cm la...