Discrete-time speech processing with application to emotion recognition

The subject of this PhD thesis is the efficient and robust processing and analysis of the audio recordings that are derived from a call center. The thesis is comprised of two parts. The first part is dedicated to dialogue/non-dialogue detection and to speaker segmentation. The systems that are developed are prerequisite for detecting (i) the audio segments that actually contain a dialogue between the system and the call center customer and (ii) the change points between the system and the customer. This way the volume of the audio recordings that need to be processed is significantly reduced, while the system is automated. To detect the presence of a dialogue several systems are developed. This is the first effort found in the international literature that the audio channel is exclusively exploited. Also, it is the first time that the speaker utterance ...

Kotti, Margarita — Aristotle University of Thessaloniki


Emotion assessment for affective computing based on brain and peripheral signals

Current Human-Machine Interfaces (HMI) lack of “emotional intelligence”, i.e. they are not able to identify human emotional states and take this information into account to decide on the proper actions to execute. The goal of affective computing is to fill this lack by detecting emotional cues occurring during Human-Computer Interaction (HCI) and synthesizing emotional responses. In the last decades, most of the studies on emotion assessment have focused on the analysis of facial expressions and speech to determine the emotional state of a person. Physiological activity also includes emotional information that can be used for emotion assessment but has received less attention despite of its advantages (for instance it can be less easily faked than facial expressions). This thesis reports on the use of two types of physiological activities to assess emotions in the context of affective computing: the activity ...

Chanel, Guillaume — University of Geneva


Realtime and Accurate Musical Control of Expression in Voice Synthesis

In the early days of speech synthesis research, understanding voice production has attracted the attention of scientists with the goal of producing intelligible speech. Later, the need to produce more natural voices led researchers to use prerecorded voice databases, containing speech units, reassembled by a concatenation algorithm. With the outgrowth of computer capacities, the length of units increased, going from diphones to non-uniform units, in the so-called unit selection framework, using a strategy referred to as 'take the best, modify the least'. Today the new challenge in voice synthesis is the production of expressive speech or singing. The mainstream solution to this problem is based on the “there is no data like more data” paradigm: emotionspecific databases are recorded and emotion-specific units are segmented. In this thesis, we propose to restart the expressive speech synthesis problem, from its original voice ...

D' Alessandro, N. — Universite de Mons


Computational models of expressive gesture in multimedia systems

This thesis focuses on the development of paradigms and techniques for the design and implementation of multimodal interactive systems, mainly for performing arts applications. The work addresses research issues in the fields of human-computer interaction, multimedia systems, and sound and music computing. The thesis is divided into two parts. In the first one, after a short review of the state-of-the-art, the focus moves on the definition of environments in which novel forms of technology-integrated artistic performances can take place. These are distributed active mixed reality environments in which information at different layers of abstraction is conveyed mainly non-verbally through expressive gestures. Expressive gesture is therefore defined and the internal structure of a virtual observer able to process it (and inhabiting the proposed environments) is described in a multimodal perspective. The definition of the structure of the environments, of the virtual ...

Volpe, Gualtiero — University of Genova


Central and peripheral mechanisms: a multimodal approach to understanding and restoring human motor control

All human actions involve motor control. Even the simplest movement requires the coordinated recruitment of many muscles, orchestrated by neuronal circuits in the brain and the spinal cord. As a consequence, lesions affecting the central nervous system, such as stroke, can lead to a wide range of motor impairments. While a certain degree of recovery can often be achieved by harnessing the plasticity of the motor hierarchy, patients typically struggle to regain full motor control. In this context, technology-assisted interventions offer the prospect of intense, controllable and quantifiable motor training. Yet, clinical outcomes remain comparable to conventional approaches, suggesting the need for a paradigm shift towards customized knowledge-driven treatments to fully exploit their potential. In this thesis, we argue that a detailed understanding of healthy and impaired motor pathways can foster the development of therapies optimally engaging plasticity. To this ...

Kinany, Nawal — Ecole Polytechnique Fédérale de Lausanne (EPFL)


Mixed structural models for 3D audio in virtual environments

In the world of Information and communications technology (ICT), strategies for innovation and development are increasingly focusing on applications that require spatial representation and real-time interaction with and within 3D-media environments. One of the major challenges that such applications have to address is user-centricity, reflecting e.g. on developing complexity-hiding services so that people can personalize their own delivery of services. In these terms, multimodal interfaces represent a key factor for enabling an inclusive use of new technologies by everyone. In order to achieve this, multimodal realistic models that describe our environment are needed, and in particular models that accurately describe the acoustics of the environment and communication through the auditory modality are required. Examples of currently active research directions and application areas include 3DTV and future internet, 3D visual-sound scene coding, transmission and reconstruction and teleconferencing systems, to name but ...

Geronazzo, Michele — University of Padova


Contributions to Human Motion Modeling and Recognition using Non-intrusive Wearable Sensors

This thesis contributes to motion characterization through inertial and physiological signals captured by wearable devices and analyzed using signal processing and deep learning techniques. This research leverages the possibilities of motion analysis for three main applications: to know what physical activity a person is performing (Human Activity Recognition), to identify who is performing that motion (user identification) or know how the movement is being performed (motor anomaly detection). Most previous research has addressed human motion modeling using invasive sensors in contact with the user or intrusive sensors that modify the user’s behavior while performing an action (cameras or microphones). In this sense, wearable devices such as smartphones and smartwatches can collect motion signals from users during their daily lives in a less invasive or intrusive way. Recently, there has been an exponential increase in research focused on inertial-signal processing to ...

Gil-Martín, Manuel — Universidad Politécnica de Madrid


Non-rigid Registration-based Data-driven 3D Facial Action Unit Detection

Automated analysis of facial expressions has been an active area of study due to its potential applications not only for intelligent human-computer interfaces but also for human facial behavior research. To advance automatic expression analysis, this thesis proposes and empirically proves two hypotheses: (i) 3D face data is a better data modality than conventional 2D camera images, not only for being much less disturbed by illumination and head pose effects but also for capturing true facial surface information. (ii) It is possible to perform detailed face registration without resorting to any face modeling. This means that data-driven methods in automatic expression analysis can compensate for the confounding effects like pose and physiognomy differences, and can process facial features more effectively, without suffering the drawbacks of model-driven analysis. Our study is based upon Facial Action Coding System (FACS) as this paradigm ...

Savran, Arman — Bogazici University


Biosignal processing and activity modeling for multimodal human activity recognition

This dissertation's primary goal was to systematically study human activity recognition and enhance its performance by advancing human activities' sequential modeling based on HMM-based machine learning. Driven by these purposes, this dissertation has the following major contributions: The proposal of our HAR research pipeline that guides the building of a robust wearable end-to-end HAR system and the implementation of the recording and recognition software Activity Signal Kit (ASK) according to the pipeline; Collecting several datasets of multimodal biosignals from over 25 subjects using the self-implemented ASK software and implementing an easy mechanism to segment and annotate the data; The comprehensive research on the offline HAR system based on the recorded datasets and the implementation of an end-to-end real-time HAR system; A novel activity modeling method for HAR, which partitions the human activity into a sequence of shared, meaningful, and activity ...

Liu, Hui — University of Bremen


Camera based motion estimation and recognition for human-computer interaction

Communicating with mobile devices has become an unavoidable part of our daily life. Unfortunately, the current user interface designs are mostly taken directly from desktop computers. This has resulted in devices that are sometimes hard to use. Since more processing power and new sensing technologies are already available, there is a possibility to develop systems to communicate through different modalities. This thesis proposes some novel computer vision approaches, including head tracking, object motion analysis and device ego-motion estimation, to allow efficient interaction with mobile devices. For head tracking, two new methods have been developed. The first method detects a face region and facial features by employing skin detection, morphology, and a geometrical face model. The second method, designed especially for mobile use, detects the face and eyes using local texture features. In both cases, Kalman filtering is applied to estimate ...

Hannuksela, Jari — University of Oulou


Performative Statistical Parametric Speech Synthesis Applied To Interactive Designs

This dissertation introduces interactive designs in the context of statistical parametric synthesis. The objective is to develop methods and designs that enrich the Human-Computer Interaction by enabling computers (or other devices) to have more expressive and adjustable voices. First, we tackle the problem of interactive controls and present a novel method for performative HMM-based synthesis (pHTS). Second, we apply interpolation methods, initially developed for the traditional HMM-based speech synthesis system, in the interactive framework of pHTS. Third, we integrate articulatory control in our interactive approach. Fourth, we present a collection of interactive applications based on our work. Finally, we unify our research into an open source library, Mage. To our current knowledge Mage is the first system for interactive programming of HMM-based synthesis that allows realtime manipulation of all speech production levels. It has been used also in cases that ...

Astrinaki, Maria — University of Mons


Artificial Bandwidth Extension of Telephone Speech Signals Using Phonetic A Priori Knowledge

The narrowband frequency range of telephone speech signals originally caused by former analog transmission techniques still leads to frequent acoustical limitations in today’s digital telephony systems. It provokes muffled sounding phone calls with reduced speech intelligibility and quality. By means of artificial speech bandwidth extension approaches, missing frequency components can be estimated and reconstructed. However, the artificially extended speech bandwidth typically suffers from annoying artifacts. Particularly susceptible to this are the fricatives /s/ and /z/. They can hardly be estimated based on the narrowband spectrum and are therefore easily confusable with other phonemes as well as speech pauses. This work takes advantage of phonetic a priori knowledge to optimize the performance of artificial bandwidth extension. Both the offline training part conducted in advance and the main processing part performed later on shall be thereby provided with important phoneme information. As ...

Bauer, Patrick Marcel — Institute for Communications Technology, Technical University Braunschweig


Statistical Parametric Speech Synthesis Based on the Degree of Articulation

Nowadays, speech synthesis is part of various daily life applications. The ultimate goal of such technologies consists in extending the possibilities of interaction with the machine, in order to get closer to human-like communications. However, current state-of-the-art systems often lack of realism: although high-quality speech synthesis can be produced by many researchers and companies around the world, synthetic voices are generally perceived as hyperarticulated. In any case, their degree of articulation is fixed once and for all. The present thesis falls within the more general quest for enriching expressivity in speech synthesis. The main idea consists in improving statistical parametric speech synthesis, whose most famous example is Hidden Markov Model (HMM) based speech synthesis, by introducing a control of the articulation degree, so as to enable synthesizers to automatically adapt their way of speaking to the contextual situation, like humans ...

Picart, Benjamin — Université de Mons (UMONS)


Facial Feature Extraction and Estimation of Gaze Direction in Human-Computer Interaction

In the modern age of information, there is a growing interest in improving interaction between humans and computers in an unremitting attempt to render it as seamless as the interaction between humans. In the core of this endeavor are the study of the human face and the focus of attention, determined by the eye gaze. The main objective of the current thesis is to develop accurate and reliable methods for extracting facial information, localizing the positions of the eye centers and performing tracking of the eye gaze. Usually such systems are grounded upon various assumptions regarding the topology of the features and the camera parameters or require dedicated hardware. In the regard of ubiquitous computing, all the methods developed in the scope of the current thesis use images and videos acquired using standard cameras under natural illumination, without the requirement ...

Skodras, Evangelos — University of Patras


Revisiting face processing with light field images

Nowadays, in a time where cities contain millions of people and where travelling across the world is becoming easier and easier, the necessity of automatically identifying a person is starting to be compelling. The physical appearance and the behavioural characteristics have been discovered useful to univocally describe a person. The analytic study of the human body measures with the aim of recognising or verifying the identity of a person, is called biometrics, literally "life measure". In the last century, several biometric traits have been investigated according to the most updated technologies available at the moment, improving recognition, computational time and memory capacity. Starting from the 90’s, research on biometrics has received a huge boost thanks to the interest raised by academic institutions, government agencies and private companies. Moreover, the diffusion of new instruments, able to perform faster analyses, and to ...

CHIESA Valeria — EURECOM Sophia Antipolis

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