Manipulating synthetic voice parameters for navigation in hierarchical structures

Presented at the 11th International Conference on Auditory Display (ICAD2005)Auditory interfaces commonly use synthetic speech for conveying information. In many instances the information being conveyed is hierarchically structured, such as menus. In this paper, we describe the results of one experiment that was designed to investigate the use of multiple synthetic voices for representing hierarchical information. A hierarchy of 27 nodes was created (in which 2 of the nodes were not shown to the participants during the training session). A between subjects design (N-16) was conducted to evaluate the effect of multiple synthetic voices on recall rates. Two different forms of training were provided. Participant's tasks involved identifying the position of nodes in the hierarchy by listening to the synthetic voice. The results suggest that 84.38% of the participants recalled the position of the nodes accurately. The results also indicate that multiple synthetic voices can be used to facilitate navigation hierarchies. Overall, this study suggests that it is possible to use synthetic voices to represent hierarchies

How do we think : Modeling Interactions of Perception and Memory

A model of artificial perception based on self-organizing data into hierarchical structures is generalized to abstract thinking. This approach is illustrated using a two-level perception model, which is justified theoretically and tested empirically. The model can be extended to an arbitrary number of levels, with abstract concepts being understood as patterns of stable relationships between data aggregates of high representation levels

Deep Learning Techniques for Music Generation -- A Survey

This paper is a survey and an analysis of different ways of using deep learning (deep artificial neural networks) to generate musical content. We propose a methodology based on five dimensions for our analysis: Objective - What musical content is to be generated? Examples are: melody, polyphony, accompaniment or counterpoint. - For what destination and for what use? To be performed by a human(s) (in the case of a musical score), or by a machine (in the case of an audio file). Representation - What are the concepts to be manipulated? Examples are: waveform, spectrogram, note, chord, meter and beat. - What format is to be used? Examples are: MIDI, piano roll or text. - How will the representation be encoded? Examples are: scalar, one-hot or many-hot. Architecture - What type(s) of deep neural network is (are) to be used? Examples are: feedforward network, recurrent network, autoencoder or generative adversarial networks. Challenge - What are the limitations and open challenges? Examples are: variability, interactivity and creativity. Strategy - How do we model and control the process of generation? Examples are: single-step feedforward, iterative feedforward, sampling or input manipulation. For each dimension, we conduct a comparative analysis of various models and techniques and we propose some tentative multidimensional typology. This typology is bottom-up, based on the analysis of many existing deep-learning based systems for music generation selected from the relevant literature. These systems are described and are used to exemplify the various choices of objective, representation, architecture, challenge and strategy. The last section includes some discussion and some prospects.Comment: 209 pages. This paper is a simplified version of the book: J.-P. Briot, G. Hadjeres and F.-D. Pachet, Deep Learning Techniques for Music Generation, Computational Synthesis and Creative Systems, Springer, 201

Morphological and population genomic evidence that human faces have evolved to signal individual identity.

Facial recognition plays a key role in human interactions, and there has been great interest in understanding the evolution of human abilities for individual recognition and tracking social relationships. Individual recognition requires sufficient cognitive abilities and phenotypic diversity within a population for discrimination to be possible. Despite the importance of facial recognition in humans, the evolution of facial identity has received little attention. Here we demonstrate that faces evolved to signal individual identity under negative frequency-dependent selection. Faces show elevated phenotypic variation and lower between-trait correlations compared with other traits. Regions surrounding face-associated single nucleotide polymorphisms show elevated diversity consistent with frequency-dependent selection. Genetic variation maintained by identity signalling tends to be shared across populations and, for some loci, predates the origin of Homo sapiens. Studies of human social evolution tend to emphasize cognitive adaptations, but we show that social evolution has shaped patterns of human phenotypic and genetic diversity as well

A synthetic approach to the classification of music. Review article

This paper first reviews the advantages and disadvantages associated with both pre-coordination and post-coordination in classification. It then argues that we can have the advantages of both if we couple a post-coordinated (synthetic) approach to classification with a user interface that privileges the word order in search queries. Several other advantages of such an approach to classification and search are reviewed. It better captures the nature of a work (or object), addresses important issues with respect to social diversity, and facilitates user queries. It produces subject strings that resemble sentence fragments; this serves to clarify the meaning of terms within the subject string, and makes subject strings more comprehensible since humans typically think in sentences. These various benefits are then illustrated in the classification of works of music. It is shown that many important characteristics of works of music are best handled by such a system. These are generally poorly addressed, or not addressed at all, by existing approaches to the classification of music

THE USE OF REGRESSION MODELS FOR DETECTING DIGITAL FINGERPRINTS IN SYNTHETIC AUDIO

Modern advancements in text to speech and voice conversion techniques make it increasingly difficult to distinguish an authentic voice from a synthetically generated voice. These techniques, though complex, are relatively easy to use, even for non-technical users. It is important to develop mechanisms for detecting false content that easily scale to the size of the monitoring requirement. Current approaches for detecting spoofed audio are difficult to scale because of their processing requirements. Individually analyzing spectrograms for aberrations at higher frequencies relies too much on independent verification and is more resource intensive. Our method addresses the resource consideration by only looking at the residual differences between an audio file’s smoothed signal and its actual signal. We conjecture that natural audio has greater variance than spoofed audio because spoofed audio’s generation is conditioned on trying to mimic an existing pattern. To test this, we develop a classifier that distinguishes between spoofed and real audio by analyzing the differences in residual patterns between audio files.Outstanding ThesisMajor, United States ArmyApproved for public release. Distribution is unlimited

Arrival of the Fittest

Prometheus, the fifth film of the Alien franchise, maintains narrative connections to the original four films but the inclusion of new aliens—the Engineers—radically shifts the feminist politic of the series. There is a move away from centralising the monster and the repressed feminine, through images of horror and bodily abjection, toward a politic of carnival, seen in representations of multiple grotesque bodies and subversion of the affect of primal scenes. Carnival is a space where the authority and stability of current social powers and orders are challenged and subverted. This article contends that in Prometheus such a process occurs in the deliberate mixing of scientific knowledge and religious cosmologies, the ambivalent relationship of horror and SF genres to science and scientific knowledge, the gendered complexities of the specific bodies of astronauts and of scientists, and disruptions of the notion of gaze and viewer positioning in the opening scenes