SIPPRE

Assistant Professor @ECE UoP

Presentation of Diploma Thesis by Ioannis Frouzis and Dimitrios Volakis

/ / Thesis Presentations

We are excited to announce the successful completion and presentation of the diploma thesis by Ioannis Frouzis and Dimitrios Volakis, titled:

“Μελέτη και ανάπτυξη συστήματος αναγνώρισης συναισθήματος τραγουδιών με χρήση τεχνικών μηχανικής μάθησης”
(“Song Emotion Recognition Using Machine Learning Techniques”)

This groundbreaking work involved the creation of a system capable of automatically recognizing emotions in songs using advanced machine learning techniques. A major highlight of the project was the development of the first-ever database of traditional Greek songs from various regions across Greece, a valuable resource for future research in this domain.

The students employed pre-trained neural networks and classifiers, leveraging diverse acoustic features to build a robust emotion recognition system. Their innovative approach not only advances the field of music analysis but also highlights the emotional depth and cultural significance of Greek traditional music.

We are proud to share that Ioannis and Dimitrios will continue their work as members of the SIPPRE Lab, further refining and expanding this important project. Their efforts exemplify the lab’s commitment to integrating technology with cultural preservation and innovation.

Congratulations to Ioannis Frouzis and Dimitrios Volakis for their exceptional contributions! We look forward to seeing how this research evolves in the future.

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Call for Participants – Binaural Sounds and EEG Activity Study

/ / Experiments

We are inviting participants to take part in an exciting research project exploring the effects of binaural sounds on brain activity, conducted by the SIPPRE Lab. This study, supervised by Prof. Athanasios Koutras, involves recording EEG signals while listening to binaural audio to investigate how different sound frequencies influence brain rhythms and physiological responses.

About the Study

The study aims to understand how binaural sounds—acoustic illusions created by presenting slightly different frequencies to each ear—affect brainwave patterns and overall brain function. This research is a part of our ongoing efforts to advance knowledge in auditory neuroscience and its applications.

Participant Information

  • Duration: Approximately 1 hour.
  • Activities: Participants will listento audio clips with varying frequencies while their brain activity is recorded using non-invasive EEG equipment. Rest periods are included to ensure comfort throughout the session.
  • Eligibility: Healthy adults aged 18–35 with normal or corrected-to-normal hearing.

What to Expect

The session will include:

  • Baseline EEG Recording: A few minutes of resting EEG recording.
  • Audio Listening: Participants will listen to carefully selected binaural sounds.
  • Feedback: An optional post-experiment questionnaire to share your experience.

Study Highlights

This project is part of the innovative work by George Patsakos and Konstantinos Anestopoulos, members of the SIPPRE Lab. Their efforts aim to push the boundaries of auditory neuroscience, combining EEG recordings with binaural sound analysis.

Join Us

If you’re interested in contributing to groundbreaking research, please contact us to schedule your session. All data will be anonymized, and participation is voluntary.

We look forward to your involvement in advancing this fascinating area of science! For further details or to sign up, please reach out via email [koutras-at-uop.gr].

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New Addition to the SIPPRE Lab: Eno Enophones

/ / Equipment

We are excited to announce the acquisition of Eno Enophones, a unique combination of high-quality headphones and EEG sensors, now available in the SIPPRE Lab. These cutting-edge devices allow us to conduct simultaneous audio-based experiments and brain activity monitoring, opening new avenues for research and student projects.

The Enophones will be utilized in various projects focused on hearing experiments and studies, including:

  • Emotion Recognition During Music Listening: Investigating how different musical genres and compositions evoke emotional responses, analyzed through EEG data.
  • Auditory Attention Studies: Exploring how the brain processes and responds to auditory stimuli, providing insights into focus and distraction in complex auditory environments.
  • Cognitive Engagement with Soundscapes: Evaluating brain activity during immersive audio experiences to understand neural responses to designed auditory environments.
  • Speech Perception and Processing: Studying the neural mechanisms involved in understanding spoken language and its relationship to cognitive load and mental states.
  • Music Therapy Research: Examining the therapeutic effects of music on emotional well-being and cognitive performance using real-time brain monitoring.

These projects will provide students with hands-on experience in neuroscience, auditory signal processing, and machine learning, using this innovative technology to bridge sound and brain research.

Stay tuned for updates on how the Enophones are driving advancements in auditory research and student-driven innovation in our lab!

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New Book Publication by Prof. Athanasios Koutras and Co-Authors

/ / Publications

We are excited to announce the publication of the new undergraduate textbook:

“Audio, Speech, and Music Processing and Analysis”

Authored by Prof. Athanasios Koutras, along with co-authors Chrisoula Alexandraki, Thomas Zarouchas, Panagiotis Zervas, and Panagiotis Chatziantoniou, this book provides a comprehensive exploration of signal processing techniques as they apply to audio, speech, and music.

Written in Greek and published by Kallipos, Open Academic Editions, the textbook is an invaluable resource for students and professionals, covering topics such as:

  • Audio Signal Processing: Fundamentals of digital sound, psychoacoustics, and room acoustics.
  • Speech Processing: Speech recognition, speaker identification, and text-to-speech synthesis.
  • Music Processing: Music Information Retrieval (MIR) and algorithmic problems in music analysis.
  • Lab Exercises: Practical projects to apply the concepts covered in the book.

With a focus on both theoretical concepts and practical applications, the book spans 304 pages and features detailed discussions on digital sound effects, audio descriptors, speech synthesis, and music analysis.

ISBN: 978-618-228-115-4
DOI: 10.57713/kallipos-347
Language: Greek

We congratulate Prof. Koutras and his collaborators on this remarkable contribution to the academic community. The book is freely available through the Kallipos repository, and we encourage everyone interested in these fields to explore this excellent resource.

For more information and access to the book, visit here.

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Presentation of Forecasting Book at the 51st Book Festival

/ / Lab News

We are excited to share that Prof. Athanasios Koutras and Prof. Ioannis Nikas presented their Greek translation of the book “Forecasting: Principles and Practice” by George Athanasopoulos and Rob J. Hyndman at the prestigious 51st Book Festival in Athens.

📅 Date: Tuesday, September 12, 2023
🕒 Time: 21:30–22:30
📍 Location: Maria Polydouri Stage, Pedion tou Areos

This event was part of the cultural activities at Greece’s largest book celebration, featuring over 210 publishers, 275 booths, and 180 cultural events. The presentation focused on the book’s essential insights into forecasting methodologies, their practical applications, and its role as a vital resource for professionals and students alike.

We thank the University of Patras Publications and the organizers of the 51st Book Festival for the opportunity to highlight this important work.

Stay tuned for more updates on our ongoing contributions to the academic and literary community!

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Congratulations to Dionysios Anyfantis for His Latest Publication

/ / Publications

We are proud to announce that Dionysios Anyfantis, PhD student and esteemed member of the SIPPRE Lab, has co-authored a significant research paper titled:

“Breast Density Transformations Using CycleGANs for Revealing Undetected Findings in Mammograms”

Published in the journal Signals (2023, Volume 4, Pages 421–438), this work introduces a novel method utilizing CycleGANs to enhance breast cancer detection by transforming dense breast tissue in mammograms to lower-density representations. This approach significantly improves the diagnostic accuracy of computer-aided systems, aiding radiologists in identifying previously masked abnormalities.

This achievement highlights the cutting-edge research happening at the SIPPRE Lab and the contributions of our dedicated members to advancing medical imaging and deep learning technologies.

Congratulations to Dionysios and the co-authors on this remarkable accomplishment! We look forward to seeing more groundbreaking work from him and the team.

For more details, you can access the full paper here.

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Keynote Presentation by Prof. Athanasios Koutras at IEEE-SB-UoP Summer School

/ / Lab News

We are delighted to announce that Prof. Athanasios Koutras, Associate Professor at the University of Peloponnese and founder of the SIPPRE Lab, delivered a keynote presentation titled:

“Revolutionizing Healthcare: The Power of AI in Saving Lives”

at the IEEE Student Branch UoP Summer School, held from May 24 to May 26, 2023, in Patras, Greece.

The presentation explored the transformative impact of Artificial Intelligence (AI) in healthcare, with a focus on:

  • Applications in medical imaging for improved diagnostics and early disease detection.
  • Recent advances in AI-driven systems for personalized medicine and predictive healthcare.
  • Ethical challenges and the importance of interdisciplinary collaboration in the evolving landscape of AI in healthcare.
  • Research contributions from the SIPPRE Lab, including innovative work on biomedical signal processing and Brain-Computer Interfaces (BCIs).

This engaging talk offered attendees a deep dive into how AI is shaping the future of healthcare and enhancing patient outcomes.

Congratulations to Prof. Koutras for sharing his expertise and inspiring the next generation of researchers and engineers!

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Enhanced EEG Capabilities in the SIPPRE Lab

/ / Equipment

We are excited to announce a significant enhancement to the EEG research capabilities in the SIPPRE Lab. Along with our existing OpenBCI Cyton and Ganglion EEG recorders, we have recently acquired the Gel-Free BCI Cap Kit, designed to deliver high-quality, reliable signals with enhanced comfort for participants.

With this new setup, we’re ready to dive deeper into exciting projects, such as:

  • Brain-Computer Interface (BCI) Applications: Using brain signals to control devices like drones, robotic arms, or even virtual environments.
  • Emotion Recognition: Exploring how brain activity reflects emotions and applying it to fields like stress management and mental health.
  • Cognitive Load and Focus Studies: Understanding how our brains handle complex tasks, with potential applications in gaming, education, and workplace productivity.
  • Music and Sound Perception: Investigating how our brains react to music and sounds, from emotional responses to cognitive engagement.
  • Motor Imagery Research: Improving how brain signals are captured during imagined movements, enhancing BCIs for gaming and rehabilitation.

This upgrade makes it easier for both students and researchers to conduct high-quality EEG experiments, whether for final diploma projects or groundbreaking studies in neuroscience, signal processing, or machine learning.

We’re looking forward to sharing the exciting discoveries that will come out of this enhanced setup—stay tuned!

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New Addition to the SIPPRE Lab: EmotiBit Sensor

/ / Equipment

We are proud to announce the latest addition to the SIPPRE Lab’s suite of equipment: the EmotiBit sensor. This wearable device provides a powerful platform for real-time physiological data acquisition, enabling researchers and students to explore a wide range of applications in emotion and health monitoring.

The EmotiBit sensor will be used in several innovative projects, including:

  • Emotion Monitoring During Media Interaction: Capturing physiological responses such as heart rate, skin conductance, and temperature while participants engage with music, videos, or other media to study emotional dynamics.
  • Stress and Relaxation Studies: Investigating physiological markers of stress and relaxation, and designing interventions to improve well-being.
  • Human-Computer Interaction (HCI): Using real-time emotional data to enhance the adaptiveness and usability of systems by responding to the user’s emotional state.
  • Computer Gaming Research: Examining player engagement, stress, and emotional responses during gaming sessions to inform game design, improve user experiences, and even develop biofeedback-based gaming.
  • Educational Research: Assessing cognitive and emotional responses during learning activities to optimize teaching methods and materials.
  • Multi-Signal Integration Projects: Combining EmotiBit data with EEG signals for advanced studies in brain-body interactions, such as exploring how physiological changes correlate with neural activity.

The EmotiBit sensor will also serve as a valuable tool for final diploma thesis projects, enabling students to gain hands-on experience with wearable technologies, physiological signal processing, and machine learning.

Stay tuned for updates on the exciting research that will emerge from the integration of EmotiBit into our lab’s activities!

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Θεματικές περιοχές διπλωματικών εργασιών

/ / Diploma Theses

Η ομάδα Αναγνώρισης Προτύπων, Επεξεργασίας Σήματος και Εικόνων (SIPPRE Group) υποστηρίζει την εκπόνηση θεμάτων διπλωματικών εργασιών στις παρακάτω θεματικές περιοχές:

  • Ψηφιακή Επεξεργασία Εικόνων
  • Ψηφιακή Επεξεργασία και Ανάλυση Ήχου
  • Ψηφιακή Επεξεργασία και Αναγνώριση Ομιλίας
  • Ανάκτηση Μουσικής Πληροφορίας
  • Επεξεργασία Βιοϊατρικού σήματος και εικόνων
  • Διερευνητική Ανάλυση Δεδομένων
  • Αναγνώριση Προτύπων και Τεχνικές Βαθιάς Μηχανικής Μάθησης
  • Σχεδιασμός και Υλοποίηση Παιχνιδιών Υπολογιστή
  • Ανάλυση και Πρόβλεψη Τουριστικών δεδομένων.

Ενδεικτικά θέματα που έχουν υποστηριχθεί ή υποστηρίζονται από την Ερευνητική Ομάδα είναι:

Ανάλυση Βιοϊατρικού Σήματος και Εικόνων

  • Έλεγχος οδήγησης ρομποτικής συσκευής με χρήση διεπαφής εγκεφάλου-υπολογιστή (brain computer interface).
  • Αναγνώριση καρκίνου σε ψηφιακές μαστογραφίες με χρήση τεχνικών βαθιάς μηχανικής μάθησης
  • Ανάπτυξη και υλοποίηση σοβαρού παιχνιδιού για την εκπαίδευση χρηστών στη χρήση συσκευών διεπαφής εγκεφάλου μηχανής (brain computer interface).

Επεξεργασία και Ανάλυση Ήχου

  • Μελέτη και υλοποίηση συστήματος αναγνώρισης συναισθήματος σχολιαστή αθλητικών αγώνων.
  • Μελέτη και ανάπτυξη συστήματος αναγνώρισης μουσικού είδους τραγουδιών
  • Μελέτη και υλοποίηση συστήματος σύστασης για την δημιουργία προτεινόμενων λιστών μουσικών κομματιών
  • Διερευνητική ανάλυση και σύγκριση ειδών metal μουσικής από περιοχές της Ευρώπης, της Αμερικής και της Ασίας.
  • Μελέτη και ανάπτυξη συστήματος αναγνώρισης ηχητικών συμβάντων χρησιμοποιώντας τεχνικές μηχανικής μάθησης.

Ανάκτηση και Ανάλυση Μουσικής Πληροφορίας

  • Μελέτη και ανάπτυξη συστήματος αναγνώρισης συναισθήματος τραγουδιών με χρήση τεχνικών μηχανικής μάθησης.
  • Μελέτη και ανάπτυξη συστήματος αναγνώρισης μουσικού είδους τραγουδιών
  • Μελέτη και υλοποίηση συστήματος σύστασης για την δημιουργία προτεινόμενων λιστών μουσικών κομματιών
  • Διερευνητική ανάλυση και σύγκριση ειδών metal μουσικής από περιοχές της Ευρώπης, της Αμερικής και της Ασίας.

Computer Games Design / Virtual Reality / Augmented Reality

  • Σχεδιασμός και Ανάπτυξη Εικονικού Περιβάλλοντος με Χρήση της Μηχανής UNITY
  • Σχεδιασμός και ανάπτυξη εικονικού περιβάλλοντος με χρήση της μηχανής id Tech 3.
  • Εφαρμογές συστημάτων εικονικής και επαυξημένης πραγματικότητας στον τομέα του τουρισμού
  • Ανάπτυξη και υλοποίηση σοβαρού παιχνιδιού για τον χώρο του πολιτισμού.
  • Σχεδιασμός και ανάπτυξη πολυμεσικής εφαρμογής με ενσωμάτωση τεχνικών επαυξημένης πραγματικότητας.

Ανάλυση και Πρόβλεψη Τουριστικών Δεδομένων

  • Γεωγραφική χωρο-χρονική ανάλυση και απεικόνιση τουριστικών δεδομένων
  • Πρόβλεψη και ανάλυση τουριστικής κίνησης σημαντικών τουριστικών προορισμών χρησιμοποιώντας τεχνικές μηχανικής μάθησης.

Αναγνώριση Προτύπων / Τεχνικές Βαθιάς Μηχανικής Μάθησης

  • Ανάπτυξη συστήματος αναγνώρισης χαρακτηριστικών της περιοχής των πωλήσεων βιβλίων μέσω τεχνικών μηχανικής μάθησης.
  • Πρόβλεψη εμπορικής επιτυχίας ταινιών με χρήση τεχνικών μηχανικής μάθησης
  • Ανάπτυξη συστήματος αναγνώρισης νοηματικής γλώσσας μέσω μηχανικής μάθησης
  • Ανάπτυξη συστηματος πρόβλεψης αλληλεπίδρασης χρηστών με πολυμεσικές αναρτήσεις σε μέσα κοινωνικής δικτύωσης χρησιμοποιώντας τεχνικές βαθιάς μάθησης.
  • Αναγνώριση βασικών δραστηριοτήτων με χρήση αισθητήρων έξυπνου τηλεφώνου και τεχνικών μηχανικής μάθησης.

Διερευνητική Ανάλυση Δεδομένων

  • Συλλογή, διερευνητική ανάλυση στατιστικών δεδομένων και υλοποίηση μεθόδων πρόβλεψης αποτελεσμάτων πρωταθλήματος ποδοσφαίρου.
  • Συλλογή και διερευνητική ανάλυση στατιστικών δεδομένων του πρωταθλήματος του ΝΒΑ
  • Συλλογή και διερευνητική ανάλυση δεδομένων εθνικών πρωταθλημάτων ποδοσφαίρου.

Για περισσότερες πληροφορίες, μπορείτε να επικοινωνειτε με τον υπεύθυνο της Ομάδας Αναπλ. Καθηγητή Κούτρα Αθανάσιο (Γραφείο Κ1.03) ή στο koutras [AT] uop.gr

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