- Music Technology and Sound Studies
- Speech and Audio Processing
- Music and Audio Processing
- Advanced Adaptive Filtering Techniques
- Acoustic Wave Phenomena Research
- Digital Filter Design and Implementation
- Hearing Loss and Rehabilitation
- Neuroscience and Music Perception
- Image and Signal Denoising Methods
- Blind Source Separation Techniques
- Advancements in PLL and VCO Technologies
- Neural Networks and Applications
- Research in Social Sciences
- Structural Health Monitoring Techniques
- Sensor Technology and Measurement Systems
- Musicians’ Health and Performance
- Analog and Mixed-Signal Circuit Design
- Vibration and Dynamic Analysis
- Speech Recognition and Synthesis
- Underwater Acoustics Research
- Noise Effects and Management
- Diverse Musicological Studies
- Vehicle Noise and Vibration Control
- Photonic and Optical Devices
- Model Reduction and Neural Networks
Aalto University
2016-2025
Espoo Music Institute
2023
Signal Processing (United States)
2010-2022
Université Grenoble Alpes
2022
Acoustics (Norway)
2021
Universitat Jaume I
2016
National Sun Yat-sen University
2015
University of Technology
1997-2014
Nokia (Finland)
2011
University of Helsinki
2002-2008
A fractional delay filter is a device for bandlimited interpolation between samples. It finds applications in numerous fields of signal processing, including communications, array speech and music technology. We present comprehensive review FIR allpass design techniques approximation digital delay. Emphasis on simple efficient methods that are well suited fast coefficient update or continuous control the value. Various new approaches proposed several examples provided to illustrate...
The first artificial reverberation algorithms were proposed in the early 1960s, and new, improved are published regularly. These have been widely used music production since 1970s, now find applications new fields, such as game audio. This overview article provides a unified review of various approaches to digital reverberation. three main categories delay networks, convolution-based algorithms, physical room models. Delay-network convolution techniques competing popularity technology field,...
Audio equalization is a vast and active research area. The extent of means that one often cannot identify the preferred technique for particular problem. This review paper bridges those gaps, systemically providing deep understanding problems approaches in audio equalization, their relative merits applications. Digital signal processing techniques modifying spectral balance signals applications these are reviewed, ranging from classic equalizers to emerging designs based on new advances...
This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect time, because aim is run simulation using a computer. physics-based classified as mass–spring, modal, wave digital, finite difference, waveguide and source–filter models. We present basic theory discussion on possible extensions each technique. For some methods, simple model example...
In numerous applications, such as communications, audio and music technology, speech coding synthesis, antenna transducer arrays, time delay estimation, not only the sampling frequency but actual instants are of crucial importance. Digital fractional (FD) filters provide a useful building block that can be used for fine-tuning instants, i.e., implement required bandlimited interpolation. this paper an overview design techniques applications is given.
The emergence of what is called physical modeling and model-based sound synthesis closely related to the development computational simulations plucked string instruments. Historically, first approaches (Hiller Ruiz 1971a, 1971b; McIntyre Woodhouse 1979; McIntyre, Schumacher, 1983) were followed by Karplus-Strong (KS) algorithm (Karplus Strong 1983). KS was discovered as a simple technique that seemingly had nothing do with physics. Soon thereafter, Julius Smith David Jaffe showed deeper...
Augmented or mixed reality (AR/MR) is emerging as one of the key technologies in future computing. Audio cues are critical for maintaining a high degree realism, social connection, and spatial awareness various AR/MR applications, such education training, gaming, remote work, virtual gatherings to transport user an alternate world called metaverse. Motivated by wide variety listening experiences delivered over hearables, this article systematically reviews integration fundamental advanced...
This paper presents CQT-Diff, a data-driven generative audio model that can, once trained, be used for solving various different inverse problems in problem-agnostic setting. CQT-Diff is neural diffusion with an architecture carefully constructed to exploit pitch-equivariant symmetries music. achieved by preconditioning the invertible Constant-Q Transform (CQT), whose logarithmically-spaced frequency axis represents pitch equivariance as translation equivariance. The proposed method...
A nonlinear discrete-time model that simulates a vibrating string exhibiting tension modulation nonlinearity is developed. The phenomenon caused by elongation during transversal vibration. Fundamental frequency variation and coupling of harmonic modes are among the perceptually most important effects this nonlinearity. proposed extends linear bidirectional digital waveguide string. It also formulated as computationally more efficient single-delay-loop structure. method reducing computational...
The digital waveguide mesh is an extension of the one-dimensional (1-D) technique. can be used for simulation two- and three-dimensional (3-D) wave propagation in musical instruments acoustic spaces. original rectangular algorithm suffers from direction-dependent dispersion. Alternative geometries, such as triangular mesh, have been proposed previously to improve performance mesh. In this paper, we show that dispersion problem may reduced using various other techniques. These methods include...
Historically, headphones have mainly been used for analytic listening in music production and homes. During the last decade, with boom of dedicated players mobile phones, everyday use light has become highly popular. Current are also paving way more sophisticated assisted devices. Today, active noise control (ANC), equalization techniques, a hear-through function already standard part many that people commonly while traveling. It is not difficult to predict that, near future, headset will be...
An aliasing reduction method for hard-clipped sampled signals is proposed. Clipping in the digital domain causes a large amount of harmonic distortion, which not bandlimited, so spectral components generated above Nyquist limit are reflected to baseband and mixed with signal. A model an ideal bandlimited ramp function derived, leads postprocessing reduce aliasing. number samples neighborhood clipping point waveform modified simulate Gibbs phenomenon. This novel requires estimation fractional...
This article investigates the use of deep neural networks for black-box modelling audio distortion circuits, such as guitar amplifiers and pedals. Both a feedforward network, based on WaveNet model, recurrent network model are compared. To determine suitable hyperparameter configuration WaveNet, models three popular pedals were created: Ibanez Tube Screamer, Boss DS-1, Electro-Harmonix Big Muff Pi. It is also shown that minutes data sufficient training models. Real-time implementations used...
The restoration of nonlinearly distorted audio signals, alongside the identification applied memoryless nonlinear operation, is studied. paper focuses on difficult but practically important case in which both nonlinearity and original input signal are unknown. proposed method uses a generative diffusion model trained unconditionally guitar or speech signals to jointly invert system at inference time. Both function restored obtained as output. Successful example studies presented including...
Neural networks have become ubiquitous in audio effects modelling, especially for guitar amplifiers and distortion pedals. One limitation of such models is that the sample rate training data implicitly encoded model weights therefore not readily adjustable at inference. Recent work explored modifications to recurrent neural network architecture approximate a independent system, enabling processing differs from original rate. This method works well integer oversampling can reduce aliasing...