May, 29

15.30

55.309

Multi-modal hearing devices and their evaluation

By Volker Hohmann

Abstract

Spatial filtering and decomposition of sounds into acoustic source objects is increasingly investigated for speech enhancement in hearing aids. However, with increasing performance and availability of these "space aware" hearing aid algorithms, knowledge of the user’s personal listening preferences and knowledge of the attended source becomes crucial.

Here we present an algorithm, which combines information of the subject’s eye gaze with an acoustic analysis of the sound source positions to identify the attended source(s) from a mixture of sources. Gaze direction is recorded by electrooculography (EOG) combined with a head tracking system, which could in principle be integrated in hearing aids. The spatio-temporal distribution of source positions is estimated from input signals to a binaural hearing device. Beamformer techniques are then used to enhance the source (or the sources) that are estimated as being attended. By using (electro-)physiologic sensor signals to estimate attention and behavior, the hearing device becomes part of the active communication loop between environment and behaving subject.

Such closed-loop hearing devices require “subject-in-the-loop” evaluation methods, which simulate realistic interactive environments to reproduce natural behavior. This means that audio-visual signals are required that also include behavioral simulation of the sources, e.g., simulated lip movement, or simulated conversational gaze behavior. The current status of our developments towards such an audiovisual interactive lab are presented in this talk.

Project funded by DFG SFB 1330 project B1 and EU H2020 MSCA ITN No
675324 (ENRICH).

Biography

Volker Hohmann received the Physics degree (Dipl.-Phys.) and the doctorate degree in Physics (Dr. rer. nat.) from the University of Göttingen, Germany, in 1989 and 1993. From 1993-2012 he was a faculty member of the Physics Institute, Oldenburg University, Germany, and was appointed full professor at the Faculty for Medicine and Health Sciences at Oldenburg University in 2012. His research expertise is in acoustics and digital signal processing with applications to signal processing in speech processing devices, e.g., hearing aids. He is a consultant with the Hörzentrum Oldenburg GmbH and with HörTech gGmbH Oldenburg. He was a Guest Researcher at Boston University, Boston, MA, (Prof. Dr. Colburn) in 2000 and at the Technical University of Catalonia, Barcelona, Spain (Prof. Dr. C. Nadeu) in 2008. Prof. Hohmann received the Lothar-Cremer prize of the German acoustical society (DEGA) in 2008 and the German President’s Award for Technology and Innovation in 2012.

Host: Federico Sukno

May, 30

15.30

55.309

PhD Research Seminar

By Simone Tassani

Abstract

The course will start with a brief digression over the several implications that bad statistics have today over the scientific society and why every researcher should know the basic concepts behind a statistical analysis.

Biography

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

May, 31

15.30

52.S29

PhD Research Seminar

Human behaviour and machine intelligence

By Emilia Gómez

Biography

Emilia Gomez, lead scientist of the HUMAINT project at the Centre for Advanced Studies, Joint Research Centre, European Commission, and head of the MIR (Music Information Research) lab of the Music Technology Group (MTG) at UPF.

June, 4

15.30

55.309

PhD Research Seminar

By Simone Tassani

Abstract

The course will start with a brief digression over the several implications that bad statistics have today over the scientific society and why every researcher should know the basic concepts behind a statistical analysis.

Biography

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

10:30 

55.309

Invited Research Seminar 

The value of Aligning Learning Analytics with a Theory-Grounded Learning Design 

By Korah Wiley   

Abstract

Learning analytics can provide teachers with information about students’ engagement with and performance on learning tasks. When these tasks are components of a theory-grounded learning design, the associated analytics have the potential to provide teachers with insight into the learning process. In this talk, I will describe the design of such theory-grounded learning analytics. Additionally, I will present findings on how teachers used these learning analytics to develop instructional interventions. I will also present findings regarding the effect of these interventions on student learning.

Biography

Korah Wiley is a doctoral candidate in the Graduate Group in Science and Mathematics Education (SESAME) program at the University of California-Berkeley and a National Science Foundation CADRE Fellow. Prior to pursuing her doctorate, she earned a Bachelor of Science in Biochemistry, a Master of Science in Molecular Cancer Biology, and taught for over 10 years as a biology instructor at the North Carolina School of Science and Mathematics. Her time teaching inspired her current research interest to support equitable STEM classroom teaching and learning. Currently, in her dissertation work, Korah investigates how to develop learning analytic solutions that promote implementation by teachers and the development of coherent science knowledge in students.

Host: Davínia Hernandez-Leo

June, 12

15.30

52.217

PhD Research Seminar 

Profiling and automated decision making under the General Data Protection Regulation

By  Antoni Rubí-Puig

Abstract:

The session aims at discussing the rules on profiling and automated individual decision-making under the General Data Protection Regulation and at assessing their adequacy from the standpoint of the Fairness, Accountability, Transparency and Ethics (FATE) framework. Our focus will be on profiling, that is, the automated processing of personal data with the goal of evaluating certain personal aspects relating to an individual, such as for instance analyzing or predicting her performance at work, economic situation, health, personal preferences, interests, willingness to pay, reliability, behavior, location or movements.

Progresses in technology and the use of big data analytics, artificial intelligence and machine learning have made it easier to elaborate profiles. Profiling can be in the advantage of individuals and organizations as it may lead to increased efficiencies and cost savings. However, it also involves significant risks for individuals’ rights and freedoms, not only to privacy. Rules in the GDPR aim at finding a balance between those advantages and risks but the final trade-off may not be the most adequate one for the FATE framework.

Biography:

Antoni Rubí-Puig,  Associate Professor in Civil Law and Associate Director for Research at the Law Department at UPF (research group).

June, 17

15.30

55.309

Invited Research Seminar 

Spatial representations and high level descriptors for symbolic music analysis

By Louis Bigo 

Abstract

This talk focus on two computational approaches to symbolic music analysis. The first approach includes the notion of pitch/chord space, that we use to reformulate in spatial terms different musical tasks as style recognition and harmonic transformations. Musical spaces are formalized with topological structures named simplicial complexes. Elementary musical objects (for example pitches or chords) are represented by simplices that are organized according to a neighborhood relationship which translates a musical property, for example consonance. Such spatial formulation of musical structures enables the application of geometrical and topological operations, such as translations, rotations, embeddings and filtrations, that bring original approaches to music composition and analysis.
The second approach focus on the extraction of high level musicological features that can serve automated analysis of classical forms. We will discuss the detection of cadences and the retrieval of section boundaries in sonata form with different machine learning methods.

Biography

I am associate professor (maître de conférence) in computational musicology at University of Lille in the Algomus team (Algorithmic musicology) at CRIStAL laboratory since 2016. My research interests include mathematical models and machine learning for automatic music generation, analysis and classification. I received my Ph.D in Computer Science on the topic of symbolic music representations and spatial computing in 2013 at IRCAM (French Institute for Research and Coordination in Acoustics/Music) and LACL, University Paris 12. I joined the European project Learning To Create on music and machine learning from 2014 to 2016 in the Music Informatics Group at the University of Basque Country in San Sebastian, Spain.

Host: Xavier Serra

June, 19

15.30

52.S29

PhD Research Seminar 

Impact of machine intelligence in healthcare

By Sergio Sánchez-Martínez

Abstract:

This talk aims at advancing the scientific understanding of machine learning (ML) related to healthcare and at studying the impact of ML algorithms on humans, focusing on clinical decision-making. The talk will be articulated around the essential building blocks to achieving the high-level task of clinical decision-making, namely data acquisition, feature extraction, interpretation and decision support. For each of these blocks, the speaker will provide a concise review of state-of-the-art applications, followed by the challenges still to overcome and the potential benefits of their application in clinical practice. At the end, there will be a discussion on the main problems to tackle when creating algorithms to analyze clinical data and also implementation challenges, such as which interaction paradigms we should use, or the competences medical doctors should have. 

Biography:

Sergio Sánchez-Martínez, Postdoctoral Research Fellow at Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS).

July, 10

15.30

55.309

Invited Research Seminar

Facebook News Feed Integrity

By Lluís Garcia-Pueyo

Abstract: 

Facebook goal with News Feed is to show people the stories that matter most to them, every time they visit Facebook. News Feed is a personalized, ever-changing collection of photos, videos, links, and updates from the friends, family, businesses, and news sources they've connected to on Facebook. People on Facebook value meaningful, informative stories, and accurate and authentic content. Integrity teams within Facebook are responsible to maintain and enforce Community Standards that reflect our collective values for what should and should not be allowed on the platform. In this talk, I'll give an overview of how the News Feed works, and how we enforce Integrity in the News Feed, as well as the challenges in combining maximizing relevance while minimizing bad experiences. 

Biography: