Thesis type
Audio Signal Processing
Bernardini, CeriThe human genome emits a variety of “signals”, produced by applying different kinds of methods/technologies for extracting information out of it. Among them, mutations, gene expression, peaks of expressions revealing protein bindings, copy number alterations, 3D contacts, and so on. Most of genome signals can be shown aligned on the genome by using a “genome browser”, which displays the information among the genome at different levels of resolution (from each individual base up to compact representations where an entire chromosome fits on the screen). However, the collective perception of these signals for interpreting their meaning and answering specific research/clinical questions is far from trivial; among the most intriguing questions, separating the signals from genomes of healthy (wild-type) humans from those affected by diseases (and particularly cancer).
Sonification has proven effective in integrating a variety of signals and providing auditive information that, once perceived as a sound, is very informative about global properties of the underlying reality. The objective of this thesis is to apply sonification methods to genome signals, displayed and selected visually, so as to produce an interesting and new form of investigation. This master thesis will take advantage of preliminary work where sound production is integrated within a sonification platform driven by the “integrated genome browser” (IGB); it requires an open mind to interdisciplinary work with not much background in any of the cited disciplines. The thesis will take advantage from an interdisciplinary group of tutors, which includes experts in genomics, music informatics and sonification, and also professional musicians.
Audio Signal Processing
BernardiniImplementing a creative audio spatializer with binaural rendering capabilitiesFull thesis5 to 6 months Internship at ARTURIA starting in February/March 2024.
Audio Signal Processing
BernardiniVirtual Analog Modeling using Machine LearningFull thesis5 to 6 months Internship at ARTURIA starting in February/March 2024.
Audio Signal Processing
BernardiniStrategies for Clipping Prevention in Dynamic Sound FilteringFull thesis The thesis aims to validate a method capable of predicting the occurrence of clipping at the output of a network of parametric digital filters, typically used in digital audio effects. If validated, this method would enable us to continuously monitor the values that a filtering parameter can assume without causing clipping. The student will assess the effectiveness of the method, particularly in parametric equalizers, highlighting aspects of robustness and weaknesses in specific implementations when their parameters are altered during equalization.
3D audioOlivieri, Pezzoli, AntonacciNearfield filter for spherical microphone array recordingsFull thesisSpherical Microphone Arrays (SMA) are very suitable for binaural rendering and in general for spatial audio applications. In this thesis we are interested in developing new methods to filter the undesired signals in a nearfield region of the SMA.
Audio Signal Processing
Olivieri, Pezzoli, AntonacciDevelopment of acoustic simulation framework for GPUShort thesisParallel implementations speed up the computation of acoustic simulations. In this short thesis it is required to develop a Room Impulse Response renderer for Spherical Microphone Arrays for GPUs. The software will be preferrabily developed with CUDA and Python.
Required knowledge: computational acoustics (RIRs, Image Source Method, ...) and experience with practical coding.
Musical AcousticsPezzoli, CilloEnhancement of a reduced-order finite-element model of a classical guitarFull/short thesis[Thesis abroad at the Institute of Engineering and Computational Mechanics (ITM), University of Stuttgart, Germany.]
A recently developed high-fidelity finite-element guitar model combined with experimental modal analysis can successfully identify the material characteristics of already existing instruments.
Parametric Model Order Reduction (PMOR) is applied to significantly reduce the computational time of the model. During the PMOR procedure, minor simplifications to the model need to be undertaken, leading to deviations of the reduced-order model from the original model.
This thesis aims to enhance the reduced-order model via optimization and/or data-driven methods to compensate for the error term resulting from the simplifications in the reduced-order model.
Required knowledge: foundations on Finite Element Methods, in depth-knowledge of deep learning (long version).
Audio forensicsBestagini, Antonacci
Detection of text-to-speech algorithmsFull thesisNowadays, text-to-speech and voice conversion algorithms are able to produce very realistic speech signals, which can easily trick human ear. Moreover, this technology is in rapid evolution and it is not possible to take in account all new synthesis methods. It is necessary to develop effective synthetic speech detection systems able to work in open-set scenarios.
Audio forensics/Audio signal processingMezzaAdversarial Attacks in Acoustic Scene ClassificationFull thesisAcoustic scene classification (ASC) is the task of recognizing an environment from the sound it produces, i.e., given an audio file, we would like to determine where it was recorded (airport, bus, park, etc.) The deployment of ASC systems in real-life security and surveillance applications entails significant issues concerning their accountability and reliability. However, the robustness and interpretability of these methods, which are typically based on deep neural networks, is still an open problem. This thesis aims to study the effects of adversarial attacks in the context of ASC. Namely, we will investigate how these methods would react to deliberate perturbations of the audio signal designed to be small enough to trick them into failing while not being detectable by the human ear.
Musical acousticsAntonacci, Olivieri, PezzoliNearfield Acoustic Holography solver based on Physics-Informed Neural NetworkFull thesisPhysics-Informed Neural Networks (PINNs) are powerful optimizers that exploit the prior knowledge of physical laws as regularization agent also in unsupervised learning tasks.
This thesis aims at extending the recent approaches of data-driven Nearfield Acoustic Holography (NAH) with solutions based on PINN.
Audio Signal Processing
Mezza, Bernardini, SartiDeep Packet Loss Concealment for SpeechFull thesisVoice communications over the Internet have become an integral part of everyday life. However, speed is often prioritized over reliability in order to respect strict real-time constraints. Consequently, short audio segments (packets) risk being severely delayed or lost. We recently developed a hybrid Packet Loss Concealment (PLC) method combining signal-processing and deep learning techniques in a synergistic way. The method, predicting future samples from a past audio context, proved to be state of the art for real-time networked music applications. In this thesis, we will explore its performance on speech signals and evaluate it against the latest deep PLC methods, such as those presented at INTERSPEECH2022. [Required knowledge: autoregressive (AR) models; practical experience with deep learning]
Audio signal processing
Antonacci, PezzoliCharacterization and analysis of the directivity of sound sourcesFull thesis, Short thesisThe directivity is an inherent property of every sound source (e.g., a musical instrument). The goal of this thesis is to define suitable descriptors for the directivity of sound sources which can be used when comparing different directivities. Long or short thesis depends on the depth and novelty of the analysis. [Required knowledge: basic knowledge of statistical signal processing, spherical harmonics decomposition of sound field].
Audio signal processing
Antonacci, PezzoliDeep learning solution for localization of acoustic sources in the spherical harmonics domainFull thesisThe spherical harmonics representation of the sound field is a widely adopted description of spatial sound. The goal of this thesis is to devise deep learning solutions that exploit the spherical harmonics representation for the analysis of the acoustic field e.g., localization of acoustic sources. [Required knowledge: spherical harmonics decomposition of sound field, theoretical knowledge and pratical experience with deep learning]
Audio signal processing
Bernardini, GiampiccoloVacuum Tubes Modeling by means of Neural Networks in the Wave Digital DomainFull thesisRecently, we proposed a method for encompassing neural networks in Wave Digital structures for the emulation of audio analog gear. Such a methods relies on vector waves, a particular definition of waves which allows us to efficiently model multiport nonlinearities. The thesis will go deep inside the topic and will try to exploit the same methodology for the emulation of vacuum tubes (triodes, but also pethode, eptode, etc.) as, until now, the technique has been applied only to BJTs.
Audio signal processing
Bernardini, GiampiccoloDynamic Scattering Recomputation applied to Extended Fixed-Point Methods in the Wave Digital DomainFull thesisThe thesis concerns the application of the Dynamic Scattering Recomputation (DSR) method for the improvement of a particular class of wave digital iterative methods, in presence of multiple scalar nonlinearities. The application is the emulation of audio circuits in the context of Virtual Analog Modeling.
Audio signal processing
Bernardini, GiampiccoloVirtual Analog Modeling, Audio Circuit Emulation, Physical Modeling Sound Synthesis through Wave Digital FiltersFull thesis
Differential Microphone ArraysBernardini, AlbertiniTwo-Stage Differential Beamforming over Networks of Microphone ArraysFull thesis[Intership at ST Microelectronics, Agrate Brianza (BG)] Differential Microphone Arrays (DMAs) have attracted significant attention in the field of acoustic array processing due to their frequency-invariant spatial responses and small size. Recently, there has been a growing interest in systems combining the output of "local" DMA units to perform further spatial filtering. Up to now, systems composed of multiple DMA units are confined to a spatially localized area. By using a more complex sound source propagation model, the thesis will explore the development of spatial filters (beamformers) relying on multiple spatially distributed DMAs.​ The thesis will involve both theoretical and more implementative aspects.
Anomaly Detection with Time SeriesBernardini, Albertini, AugustiAnomaly Detection with Industrial IoT Nodes under Domain Shift ConditionsFull thesis[Intership at ST Microelectronics, Agrate Brianza (BG)] Anomaly detection is a critical aspect of many industries, allowing for the early detection of equipment failures or abnormalities. One major challenge lies in adapting anomaly detection systems to operate effectively in changing environments and varying conditions, where the data distribution may differ from the training data. The thesis aims to develop an anomaly detection solution by incorporating sensor fusion techniques acquired with an industrial IoT node. Specifically, the intern will focus on integrating audio and accelerometer data to create a more robust monitoring system.
Musical AcousticsAntonacci, Olivieri, PezzoliThe impact of reverberation for data-driven Nearfield Acoustic HolographyFull/short thesisRecent Deep Learning techniques proved the ability to infer the vibrational behavior in plates starting from acoustic measurements. This thesis aims at quantifying the performance of the current data-driven methods for Nearfield Acoustic Holography in the presence of reverberation (short thesis) and extending the neural network model to work in reverberant scenarios (long thesis).
Musical AcousticsAntonacci, Olivieri, PezzoliTransfer Learning techniques for Nearfield Acoustic Holography analysisFull/short thesisRecent data-driven based NAH methods can predict the vibrational behavior on sources from the acquisition of the radiated sound field. Nevertheless, these approaches are dependent on the training dataset used (i.e., acquisition setup and vibrational source). This thesis aims at extending the recent solutions with transfer learning strategies in order to tune the networks with different data and improving the model with specific physical priors to reconstruct the vibrational content with an unsupervised approach (long thesis). [knowledge of Deep Learning required]
Musical AcousticsGonzalez, Malvermi, AntonacciExperimental measurement and construction of violin top platesFull/short thesisThe aim of this thesis is twofold: measure the material properties of violin top plates and build violin top plates with certain material properties. For this the student will use a CNC router to build the plates and a experimental set up that measures the FRF of the plate to compute its material parameters. The goal is to be able to produce top plates with a defined mechanical response irrespective of the varying material parameters of the wood the top is made of. Experimental thesis in Cremona Campus, FEM modelling required, Fusion 360 optional.
Musical AcousticsGonzalez, AntonacciRole of f-hole design in stress distribution on the violin top plateLong thesisThe role of the f-holes in violins is to let the sound vibrations leave the body of the instrument and reach the audience. However, cutting holes in the top plate weakens it. By cutting curves and circles, the instrument maker avoids creating the stress concentrations associated with sharp corners. The aim of this thesis is to study the stress behaviour in a violin soundboard for different f-hole designs. Comsol experience preferred.
Musical AcousticsGonzalez, Malvermi, AntonacciEffect of tailpiece height in the acoustic response of a violinLong thesisVarying the height of the tailpiece is one of the ways luthiers can control the sound production of the violin. By changing the angle of the strings, there is a modification in the effective pressure that the bridge, and consequently the violin top plate, feels. This compression of the violin is believed to affect the sound production of the instrument. This thesis aims to study, by means of simulations, the effect the net static force in the bridge has in the dynamics of the instrument. If time allows the thesis could also include experimental measurements with the help of Amorim fine violins.
Musical AcousticsGonzalez, AntonacciLinear interpolation between shapes in western guitarsLong thesisIn one of our last thesis projects we have developed a completely parametric model of the guitar. The objective of this thesis is to study how vibrational characteristics change when smoothly varying the shape of a guitar between standard models, say between a Jumbo and a Dreadnought. The work involves the creation of different virtual models and its study with Comsol multiphysics.
Musical AcousticsGonzalez, Malvermi, AntonacciTowards 3D printed usable violinsLong thesis
Musical AcousticsGonzalez, Greco, AntonacciTimbral Study of 3D printed organ pipesLong thesisRecently, researchers have presented a theoretical model to understand the timbre of the organ by mapping its sound to a bi-dimensional map in the spectral-centroid and envelope slope of the spectra. This thesis wants to study how geometric variations in 3D printed organ pipes determine the location of the sound in this timbral map.
Musical AcousticsGonzalez, Longo, AntonacciDevelopment of online visualization tool for radiation pattern data / TAKENShort thesisPresenting the results of radiation patterns experiments and simulations is a rather complex thing to do on paper. One would like to see a 2D field that changes with frequency, and compare different patterns at different frequencies to gain insight on how the design of an instrument influences its radiation pattern. The objective of this thesis is to, using the results of previous projects, present them in an online way that takes full advantage of the multimedia nature of webpages. In particular we are thinking of a github page that can easily display the information of comsol simulations in a easy to use and understand manner.
Musical AcousticsGonzalez, Malvermi, AntonacciExperimental study of wooden metamaterials / TAKENLong thesisExperimental realisation of metamaterials for instrument making: guitar top plates, violin top plates, archtop top plates. Studies of vibrational and stiffness behaviour. Needs to live in Cremona.
Musical AcousticsGonzalez, Longo, AntonacciNeural Network-based prediction of sound fields in guitars Short thesisRecently we have shown that a neural network can accurately predict the vibrational response of guitar for different material and geometric configurations. The results for the prediction of sound pressure level are however not as good and require more training data and/or a different architecture for the neural network. This short thesis aim is to create the dataset and train the network in the expanded data.
Musical AcousticsGonzalez, Longo, AntonacciThe influence of scale length and string pre-stress in the vibrational and radiative properties of guitars / TAKENLong thesisWhen studying musical instruments researchers usually focus on the body as the main explicative feature of the instrument. The neck, however, also has an influence and different lengths are currently in production in the industry. This thesis proposes to study the effect of scale length in the vibrational and radiative properties of a guitar, together with the load bearing effects that strings of different lengths have in the instrument.
Musical AcousticsGonzalez, AntonacciDeveloping a new Manouche guitar: studying different bracings models for the gypsy jazz icon Long thesisManouche guitars are a mix between mandolins, parlour and archtop guitars. Created in Paris by Italian luthier Macaferri, they represent a particular understanding of how to make instruments. Their design takes from the parlour guitar in terms of bracing, from the archtop in its shape and floating bridge, and from the mandolin in its bent top plate. The aim of this thesis is to study, by means of simulations, different bracing patterns that could inform a new way of crafting these instruments. The selected model when then be built by one of the advisors.
Musical AcousticsGreco, AntonacciNeural Network-Based Prediction of Woodwind Mouthpiece Sound Characteristics through Finite Element Method SimulationsLong thesisThis master's thesis proposes a novel approach to explore the relationship between geometric parameters of woodwind instrument mouthpieces and their corresponding sound characteristics. Employing COMSOL Multiphysics, Finite Element Method (FEM) simulations will be conducted to assess impedance variations. Simulated geometries will be transformed into transfer matrices to create a dataset for training a neural network. The objective is to develop a predictive model capable of estimating sound behavior without explicit FEM simulations, thus offering a more efficient and accessible method for instrument design and optimization. The study aims to contribute to the field of music and acoustic engineering by reducing computational costs and time associated with traditional simulation methods.
Image and Video
Thesis type
Image/video forensicsBestagini, Mandelli, Cannas
Detect and localize image and video manipulations
FullImages and videos can be manipulated in many different ways (e.g., object insertion and removal, local retouching, laundering operations, etc.). We are interested in developing methods to detect and localize possible editing operations on images and videos.
Image/video forensicsBestagini, Mandelli, Cannas
Distinguish original videos from DeepFakesFullDeepFake videos can be maliciously spread online. We are interested in developing techniques to detect whether a video is a DeepFake or not, why a detector says a video is fake, and understand which DeepFake generation software has been used to create a video.
Image/video forensicsBestagini, Mandelli, Cannas
Assess the authenticity of satellite imagesFullSatellites can acquire visual data with different sensors. We are interested in developing techniques that verify whether an overhead image has been edited or not.
Image/video forensicsBestagini, Mandelli, Cannas
Forensic analysis of scientific imagesFullScientific publications in the life science area typically contain charcateristic kinds of images to showcase the achieved results (e.g., western blots, microscopy acquisitions, etc.). As these images differ from natural photographs, we are interested in developing novel techniques to detect possible scientific image forgery operations.
Image processingBestagini, Mandelli, GigantiEnhanceent of emission mapsFullBiogenic Volatile Organic Compounds (BVOCs) are gases emitted by plants under different leveles of stress. The study of these emissions is paramount for several applications related to environmental and pollution control. Measuring these emissions is often very challenging. It is therefore customary to only have a few sparse measurements over the area to control. The goal of this work is to apply interpolation and super-resolution techniques to fill-in the gaps in sparse emission maps.
Thesis type
Tubaro, LipariImproving Full Waveform Inversion with CNNsFull/shortFull Waveform Inversion reconstructs the subsurface velocities from a set of measurements. It is very expensive, time-consuming and prone to a number of tips and tricks for avoiding local minima, numerical instability and optimization errors.
Tubaro, LipariDenoising and Interpolation of seismic data through CNNsFull/shortThe amount of data is constantly increasing and the areas of interest are more and more complex to analyze. Moreover, they require a subsurface mapping at increasingly higher resolution and higher fidelity. Can CNNs help this process?
Tubaro, LipariMachine Learning guided Seismic InterpretationFull/shortHuman experts visually inspects seismic images looking for subsurface features. On the other hand, Machine Learning techniques have proven to be effective in image segmentation (i.e., recognizing objects and targets from a set of pixels). Can we merge these two worlds?
Tubaro, LipariPhysics-aware Transfer LearningFull/shortCan a neural network learn Physics?
Tubaro, LipariRegularizing Traveltime Tomography via Machine LearningFull/shortTraveltime Tomography is an important tool for localizing subsurface events, both in medical and geophysical imaging. The tomography problem is a ill-posed and ill-conditioned inverse problem, which suffers a lot from numberical instability, local minima, and noise. Here's where the machine learning comes into play!

Currently on-going

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Audio signal processing
Bernardini, Giampiccolo2D Canonical Piecewise-Linear functions for the Wave Digital Modeling of 2-port NonlinearitiesValerio Maiolo
3D audioPezzoli, OlivieriAcoustic Virtual Reality evaluation systemFrancesca Del Gaudio
Audio signal processingBernardini, GiampiccoloModeling of MOSFETs for Virtual Analog ApplicationsMarco Ferrè
3D audioPezzoli, OlivieriNeural Network-based representation of sound source directivityEdoardo Morena
Audio signal processingBernardini, Giampiccolo, AlbertiniAntiderivative Antialiasing for MOSFETsChristian Parra
Space-time audioPezzoli, MiotelloSpherical microphone array upsamplingFerdinando Terminiello
Space-time audioPezzoli, OlivieriSound field reconstruction for 6DoF navigationSilvio Attolini
Space-time audioAntonacci, Pezzoli, Miotello, OlivieriReal-time microphone array rendering framework for binaural reproductionPaolo Ostan
Space-time audioAntonacci, PezzoliSound field separation in the spherical harmonics domain Sagi Della-Torre
Space-time audioAntonacci, PezzoliAnalysis of the directivity of sound sourcesHou Hin Au-Yeung
Audio signal processingBernardini, GiampiccoloModeling of Nonlinear Piezoelectric LoudspeakersArmando Boemio
Image forensicsBestagini, MandelliManipulation detection for scientific imagesGiovanni Zanocco
Musical AcousticsAntonacci, OlivieriTowards white-box data-driven methods for Near-field Acoustic HolographyHagar Kafri
Music informaticsSarti, Mezza, BernardiniUnsupervised selection of harmonic complexity metricsGiorgio De Luca
Music informaticsZanoni, BorrelliSocial interaction based music recommendation systemCarlo Pulvirenti
Music informaticsSarti, BorrelliConnecting NN to bio-metric signalsJoep Rene Wulms
Musical AcousticsGonzalez, AntonacciRandom variation of guitar bracingsMattia Vanessa
Musical acousticsGonzalez, AntonacciMetamaterials for guitarmakingGabriele Marelli, Mattia Lercari
Musical acoustics / AIGonzalez, AntonacciAI-powered pick up: making guitars sound great againEmanuele Voltini
Space-time audioPezzoli, ComanducciGenerative Models for HRTF predictionJuan Camilo Albarracín Sánchez
Music InformaticsSarti, ComanducciHandMonizer, personalized digital musical instrument designAntonios Pappas
Music InformaticsComanducci, MezzaImpact of velocity on drum patterns perceived complexityGabriele Maucione
Music InformaticsComanducci, Ronchini, ZanoniPersonalized Music Generation using text-to-music modelsGabriele Perego

Past (from 2017)

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Music InformaticsZanoni, ComanducciProcedural Music Generation For Video gamesFrancesco Zumerle
Audio signal processingBernardini, Giampiccolo, MezzaOn the Use of Fundamental Frequency Estimation for Virtual Bass EnhancementFabio Spreafico
Video forensicsBestagini, CannasDeepfake video detection through multi-look analysisAdriano Bonfantini
Video processingBestagini, RedondiAutomatic video analysis of badminton matchesIvan Motasov
Space-time audioBernardini, Giampiccolo, MezzaDesigning of Scattering Delay Networks Via Automatic DifferentiationFrancesco Boarino
Audio signal processingBernardini, GiampiccoloA Wave Digital Extended Fixed-Point Method for Virtual Analog ApplicationsDavide Marin Pasin
Musical AcousticsRipamonti, Malvermi, GonzalezExperimental Validation for data-driven Near-field Acoustic HolographyAlessio Lampis
Musical AcousticsAntonacci, MalvermiImproved sensors for low-cost Vibrometric KitFabio Guarnieri
Audio signal processingBernardini, GiampiccoloA Wave Digital Hierarchical Quasi-Newton Method for Virtual Analog ModelingLuca Gobbato
Musical AcousticsSarti, Paoletti, Adali, MalvermiAcoustic Characterization of materialsMarco Donzelli
Music Informatics Zanoni, ComanducciDeep Learning-based Timbre TransferSilvio Pol
Audio signal processingAntonacciA perceptual evaluation of sound field reconstruction algorithmsMiriam Papagno
Audio signal processing
Bernardini, GiampiccoloCharacterization of Small-Size Loudspeakers for Mobile ApplicationsSamuele Buonassisi
Image forensicsBestagini, CannasEnhanced Amplitude SAR Imagery Splicing Localization through Land Cover Mapping TechniquesEmanuele Intagliata
GeophysicsBestagini, LipariSalt Segmentation of Geophysical Images through Explainable CNNsFrancesco Maffezzoli
Audio forensicsBestagini, BorrelliA metric learning approach for splicing localization based on synthetic speech detectionFrancesco Castelli
Audio forensicsBestagini, BorrelliCombining automatic speaker verification and prosody analysis for synthetic speech detectionLuigi Attorresi
Music informaticsBestagini, CuccovilloSpeech fingerprinting and matching for content retrievalLaura Colzani
Video forensicsBestaginiA CNN-based detector for video frame-rate interpolationSimone Mariani
Image/video processingBestaginiAudio-video techniques for the analysis of players behaviour in Badminton matchesSamuele Bosi
Video forensicsBestagini, MandelliForensic detection of deepfakes generated through video-to-video translationCarmelo Fascella
Audio signal processing
Bernardini, Mezza, GiampiccoloWave Digital Filter Modeling of Audio Circuits with Hysteresis Nonlinearities using Neural NetworksOliviero Massi
Music informaticsAntonacci, Pezzoli, ComanducciDeep Prior Audio InpaintingFederico Miotello
Audio signal processingBestagini, BuccoliLow-latency speaker recognitionFrancesco Salani
Video forensicsBestagini, BonettiniA Data Driven Approach to Deepfake Detection via Feature Analysis Based on Limited Data Bingyang Hu
Space-time audioAntonacci, Borrelli, BorraBeamforming and Speaker Identification through Deep Neural Networks Matteo Scerbo
Music informaticsSarti, BorrelliHarmonic complexity estimation of jazz musicGiovanni Agosti
Audio forensicsAntonacci, BorrelliA model selection method for room shape classification based on mono speech signalsGabriele Antonacci
Audio forensicsBestaginiAudio splicing detection and localization based on recording device cuesDaniele Ugo Leonzio
Audio forensicsBestaginiSpeaker-Independent Microphone Identification via Blind Channel Estimation in Noisy ConditionAntonio Giganti
Audio forensicsBestagini, BorrelliSynthetic Speech Detection through Convolutional Neural Networks in Noisy EnvironmentsEleonora Landini
Audio forensicsBestagini, Borrelli, SalviSynthetic speech detection based on sentiment analysisEmanuele Conti
Multimedia forensicsBestagini, Salvi, BorrelliAudio-video deepfake detection through emotion recognitionJacopo Gino
Audio signal processingSarti, Giampiccolo, BernardiniParallel Wave Digital Implementations of Nonlinear Audio CircuitsNatoli Antonino
Musical AcousticsAntonacci, MalvermiData driven methods for frequency response functions interpolationMatteo Acerbi
Audio forensicsBestagini, MandelliTime-Scaling Detection in Audio RecordingsMichele Pilia
Audio forensicsBestagini, BorrelliSpeech Intelligibility Parameters Estimation Through Convolutional Neural NetworksMattia Papa
Audio forensicsAntonacciClosed and open set classification of real and AI synthesised speechMichelangelo Medori
Audio forensicsAntonacciAn approach to room volume estimation from single-channel speech signals based on neural networksCastelnuovo Carlo
Audio forensicsBestaginiAudio Splicing Detection and Localization Based on Acoustic CuesCapoferri Davide
Audio processingSarti, ComanducciAudio frame reconstruction from incomplete observations using Deep Learning techniquesSchils Minh Cédric
Audio processingSarti, BernardiniWave Digital Modeling and Simulation of Nonlinear Electromagnetic CircuitsGiampiccolo Riccardo
Audio processingSarti, BernardiniAntiderivative Antialiasing in Nonlinear Wave Digital FiltersAlbertini Davide
Audio processingSarti, BernardiniWave Digital Implementation of Nonlinear Audio Circuits based on the Scattering Iterative MethodProverbio Alessandro
Audio processingAntonacciA system for super resolution vibrometric analysis through convolutional neural networksCampagnoli Chiara
Audio processingAntonacciDevelopment of a low-cost platform for acoustic and vibrometric analysis on lutherie products, with a special focus on the estimation of the elastic parameters of the tonewoodVilla Luca
Audio processingBestaginiDNN based post-filtering for quality improvement of AMR-WB decoded speechGupta Kishan
Audio processingSartiStudio sull'implementazione degli algoritmi per il musical instruments ed il sound reinforcement basato su un processore multicoreAretino Michele
Audio processingSarti, BernardiniModeling nonlinear 3-terminal devices in the wave digital domainVergani Alessio Emanuele
ForensicsBestaginiConvolutional and recurrent neural networks for video tampering detection and localizationCannas Edoardo Daniele
ForensicsBestaginiA study on Bagging-Voronoi algorithm for tampering localizationCereghetti Corinne Elena
ForensicsBestaginiJPEG-based forensics through convolutional neural networksBonettini Nicolò
ForensicsBestaginiAnalysis of different footprints for JPEG compression detectionChen Ke
GeophysicsBestaginiLandmine detection on GPR data employing convolutional autoencoderTesta Giuseppe
Image and videoMarcon, ParacchiniA novel tomographic approach for an early detection of multiple myeloma progressionAndrea Leggio
Image and videoMarcon, ParacchiniLimited angle computed tomography reconstruction with deep learning enhancementErbol Kasenov, Girolamo Gerace
Image and videoMarconUpper body postural assessment for common dentistry visual aidsTrotta Emilio
Image and videoTubaroReal-time tracking of electrode during deep-brain surgeryDilauro Valerio
Image and videoMarconAnalytical estimation of the error on the radius of industrial pipesLazzarin Sara
Image and videoMarcon3D reconstruction from stereo video acquired from odontoiatric microscopeSpatafora Leonardo
Image and videoMarconDenoising and classification of hyperspectral X-ray images for food quality assessmentRe Marco
Image and videoMarconA computer vision approach for assessment of dental bracket removalBehnami Arezoo
Image and videoMarconSistema per il rilevamento automatico di contaminanti alimentari basato su immagini iperspettraliRamoni Francesco
Image and videoMarconPostural assessment in dentistry by computer visionPignatelli Nicola
Multimedia forensicsBestagini, MandelliA Multi-Modal Approach to Forensic Audio-Visual Device IdentificationDavide Dal Cortivo
Music informaticsSarti, Bernardini, Borrelli, MezzaEstimating Harmonic Complexity of Chord Sequences using Transformer NetworksCecilia Morato
Music informaticsZanoni, ComanducciModeling Harmonic Complexity in Automatic Music Generation using Conditional Variational AutoencodersDavide Gioiosa
Music informaticsSarti, Borrelli, ComanducciCellular music : a novel music-generation platform based on an evolutionary paradigmMatteo Manzolini
Music informaticsSarti, BorrelliMusic emotion detection. A framework based on electrodermal activities.Gioele Pozzi
Music informaticsSarti, ComanducciTechniques for mitigating the impact of latency in
Networked Music Performance (NMP) through adaptive metronomes
Battello Riccardo
Music information retrievalSartiMusical instrument recognition: a transfer learning approachMolgora Andrea
Music information retrievalSartiUnsupervised domain adaptation for deep learning based acoustic scene classificationMezza Alessandro Ilic
Music information retrievalAntonacciAn investigation of piano transcription algorithm for jazz musicMarzorati Giorgio
Music information retrievalSartiAutomatic playlist generation using recurrent neural networkIrene Rosilde Tatiana
Music information retrievalSartiA personalized metric for music similarity using Siamese deep neural networksSala Federico
Music information retrievalSartiLearning a personalized similarity metric for musical contentCarloni Luca
Music information retrievalSartiBeat tracking using recurrent neural network : a transfer learning approachFiocchi Davide
Music information retrievalSartiPython-based framework for managing a base of complex data for music information retrievalAvocone Giuseppe
Music information retrievalSartiIndividual semantic modeling for music information retrievalAnsidei Pietro
Music information retrievalSartiChord sequences : evaluating the effect of complexity on preferenceFoscarin Francesco
Music information retrievalSartiAudio features compensation based on coding bitrateTavella Maria Stella
Musical AcousticsAntonacciModal analysis and optimization of the top plate of string instruments through a parametric control of their shapeSalvi Davide
Musical AcousticsAntonacci, Pezzoli, Malvermi An approach for Near-field Acoustic Holography based on Convolutional AutoencodersOlivieri Marco
Space-time audioAntonacci, BorraA parametric approach to virtual miking with distributed microphone arraysMarco Langè
Space-time audioAntonacci, Pezzoli, Borra, BernardiniA Deep Prior Approach to Room Impulse Response InterpolationDavide Perini
Space-time audioAntonacci, ComanducciInterpreting Deep Neural Networks Models for Acoustic Source Localization using Layer-wise Relevance PropagationAlessandro Montali
Space-time audioAntonacci, Borra, BernardiniAnalysis of Uniform Linear Arrays of Differential MicrophonesBertuletti Ivan
Space-time audioSartiA geometrical method of 3D sound spatialization for virtual reality applicationsIamele Jacopo
Space-time audioAntonacciConvolutional neural networks applied to space-time audio processing applicationsComanducci Luca
Space-time audioCancliniDenoising in the spherical harmonic domain of sound scenes acquired by compact arraysBorrelli Clara
Space-time audioAntonacciSimulazione di sistemi complessi. Case study : l'altoparlante a trombaMoscara Francesco
Space-time audioSarti, BernardiniSteerable differential microphone arraysLovatello Jacopo
Space-time audioAntonacciA plenacoustic approach to sound scene manipulationPicetti Francesco
Space-time audioAntonacciReconstruction of the soundfield in arbitrary locations using the distributed ray space transformPezzoli Mirco
Space-time audioSartiA method for HRTF personalization : weighted sparse representation synthesis of HRTFsZhu Mo
Space-time audioAntonacciRobust parametric spatial audio processing using beamforming techniquesMilano Guendalina
Space-time audioAntonacciEstimation of singing voice quality through microphone in air and contact microphoneLandini Roberta
Musical AcousticsAntonacci, MalvermiMechanical parameter estimation for vibrometric analysis and development of a low-cost platform for violin makingFederico Simeon
Space-time audioAntonacci, Comanducci3D audio with irregular microphone setups using deep learningDavide Mori
Space-time audioAntonacci, ComanducciPersonalized Sound Zone Generation using Deep LearningRoberto Alessandri