Information encoding by deep neural networks: what can we learn?

The recent advent of deep learning techniques in speech tech-nology and in particular in automatic speech recognition hasyielded substantial performance improvements. This suggeststhat deep neural networks (DNNs) are able to capture structurein speech data that older methods for acoustic modeling, suchas Gaussian Mixture Models and shallow neural networks failto uncover. In image recognition it is possible to link repre-sentations on the first couple of layers in DNNs to structuralproperties of images, and to representations on early layers inthe visual cortex. This raises the question whether it is possi-ble to accomplish a similar feat with representations on DNNlayers when processing speech input. In this paper we presentthree different experiments in which we attempt to untanglehow DNNs encode speech signals, and to relate these repre-sentations to phonetic knowledge, with the aim to advance con-ventional phonetic concepts and to choose the topology of aDNNs more efficiently. Two experiments investigate represen-tations formed by auto-encoders. A third experiment investi-gates representations on convolutional layers that treat speechspectrograms as if they were images. The results lay the basisfor future experiments with recursive networks

Violence and the postcolonial welfare state in France and Australia

What can analyses of violence in marginalised communities in France and Australia teach us about the evolving structures of the postcolonial welfare state? This collection originates from a workshop that was held in October 2007 at the University of Sydney for the purpose of exploring this question. It represents a conversation between scholars working on violence in Australian Aboriginal communities and those studying violence in immigrant communities in France, particularly in relation to rioting

Phase synchronization between EEG signals as a function of differences between stimuli characteristics

The neural processing of speech leads to specific patterns in the brain which can be measured as, e.g., EEG signals. When properly aligned with the speech input and averaged over many tokens, the Event Related Potential (ERP) signal is able to differentiate specific contrasts between speech signals. Well-known effects relate to the difference between expected and unexpected words, in particular in the N400, while effects in N100 and P200 are related to attention and acoustic onset effects. Most EEG studies deal with the amplitude of EEG signals over time, sidestepping the effect of phase and phase synchronization. This paper investigates the relation between phase in the EEG signals measured in an auditory lexical decision task by Dutch participants listening to full and reduced English word forms. We show that phase synchronization takes place across stimulus conditions, and that the so-called circular variance is narrowly related to the type of contrast between stimuli

Dealing with uncertain input in word learning

In this paper we investigate a computational model of word learning, that is embedded in a cognitively and ecologically plausible framework. Multi-modal stimuli from four different speakers form a varied source of experience. The model incorporates active learning, attention to a communicative setting and clarity of the visual scene. The model's ability to learn associations between speech utterances and visual concepts is evaluated during training to investigate the influence of active learning under conditions of uncertain input. The results show the importance of shared attention in word learning and the model's robustness against noise

Connected digit recognition with class specific word models

This work focuses on efficient use of the training material by selecting the optimal set of model topologies. We do this by training multiple word models of each word class, based on a subclassification according to a priori knowledge of the training material. We will examine classification criteria with respect to duration of the word, gender of the speaker, position of the word in the utterance, pauses in the vicinity of the word, and combinations of these. Comparative experiments were carried out on a corpus consisting of Dutch spoken connected digit strings and isolated digits, which are recorded in a wide variety of acoustic conditions. The results show, that classification based on gender of the speaker, position of the digit in the string, pauses in the vicinity of the training tokens, and models based on a combination of these criteria perform significantly better than the set with single models per digit

Active word learning under uncertain input conditions

This paper presents an analysis of phoneme durations of emotional speech in two languages: Dutch and Korean. The analyzed corpus of emotional speech has been specifically developed for the purpose of cross-linguistic comparison, and is more balanced than any similar corpus available so far: a) it contains expressions by both Dutch and Korean actors and is based on judgments by both Dutch and Korean listeners; b) the same elicitation technique and recording procedure were used for recordings of both languages; and c) the phonetics of the carrier phrase were constructed to be permissible in both languages. The carefully controlled phonetic content of the carrier phrase allows for analysis of the role of specific phonetic features, such as phoneme duration, in emotional expression in Dutch and Korean. In this study the mutual effect of language and emotion on phoneme duration is presented

Multiple plumage traits convey information about age and within-age-class qualities of a canopy-dwelling songbird, the Cerulean Warbler

Colorful plumage traits in birds may convey multiple, redundant, or unreliable messages about an individual. Plumage may reliably convey information about disparate qualities such as age, condition, and parental ability because discrete tracts of feathers may cause individuals to incur different intrinsic or extrinsic costs. Few studies have examined the information content of plumage in a species that inhabits forest canopies, a habitat with unique light environments and selective pressures. We investigated the information content of four plumage patches (blue-green crown and rump, tail white, and black breast band) in a canopy-dwelling species, the Cerulean Warbler (Setophaga cerulea), in relation to age, condition, provisioning, and reproduction. We found that older males displayed wider breast bands, greater tail white, and crown and rump feathers with greater blue-green (435–534 nm) chroma and hue than males in their first potential breeding season. In turn, older birds were in better condition (short and long term) and were reproductively superior to younger birds. We propose that these age-related plumage differences (i.e. delayed plumage maturation) were not a consequence of a life history strategy but instead resulted from constraints during early feather molts. Within age classes, we found evidence to support the multiple messages hypothesis. Birds with greater tail white molted tails in faster, those with more exaggerated rump plumage (lower hue, greater blue-green chroma) provisioned more, and those with lower rump blue-green chroma were in better condition. Despite evidence of reliable signaling in this species, we found no strong relationships between plumage and reproductive performance, potentially because factors other than individual differences more strongly influenced fecundity

Spatial variation in breeding habitat selection by Cerulean Warblers (Setophaga cerulea) throughout the appalachian mountains

Studies of habitat selection are often of limited utility because they focus on small geographic areas, fail to examine behavior at multiple scales, or lack an assessment of the fitness consequences of habitat decisions. These limitations can hamper the identification of successful site-specific management strategies, which are urgently needed for severely declining species like Cerulean Warblers (Setophaga cerulea). We assessed how breeding habitat decisions made by Cerulean Warblers at multiple scales, and the subsequent effects of these decisions on nest survival, varied across the Appalachian Mountains. Selection for structural habitat features varied substantially among areas, particularly at the territory scale. Males within the least-forested landscapes selected microhabitat features that reflected more closed-canopy forest conditions, whereas males in highly forested landscapes favored features associated with canopy disturbance. Selection of nest-patch and nest-site attributes by females was more consistent across areas, with females selecting for increased tree size and understory cover and decreased basal area and midstory cover. Floristic preferences were similar across study areas: White Oak (Quercus alba), Cucumber-tree (Magnolia acuminata), and Sugar Maple (Acer saccharum) were preferred as nest trees, whereas red oak species (subgenus Erythrobalanus) and Red Maple (A. rubrum) were avoided. The habitat features that were related to nest survival also varied among study areas, and preferred features were negatively associated with nest survival at one area. Thus, our results indicate that large-scale spatial heterogeneity may influence local habitat-selection behavior and that it may be necessary to articulate site-specific management strategies for Cerulean Warblers