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Audio bandwidth extension aims to expand the spectrum of narrow-band audio signals. Although this topic has been broadly studied during recent years, the particular problem of extending the bandwidth of historical music recordings remains an open challenge. This paper proposes BEHM-GAN, a model based on generative adversarial networks, as a practical solution to this problem. The proposed method works with the complex spectrogram representation of audio and, thanks to a dedicated regularization strategy, can effectively extend the bandwidth of out-of-distribution real historical recordings. The BEHM-GAN is designed to be applied as a second step after denoising the recording to suppress any additive disturbances, such as clicks and background noise. We train and evaluate the method using solo piano classical music. The proposed method outperforms the compared baselines in both objective and subjective experiments. The results of a formal blind listening test show that BEHM-GAN significantly increases the perceptual sound quality in early-20th-century gramophone recordings. For several items, there is a substantial improvement in the mean opinion score after enhancing historical recordings with the proposed bandwidth-extension algorithm. This study represents a relevant step toward data-driven music restoration in real-world scenarios., Comment: Accepted at IEEE Transactions on Audio, Speech, and Language Processing

When a person listens to loudspeakers, the perceived sound is affected not only by the loudspeaker properties but also by the acoustics of the surroundings. Loudspeaker equalization can be used to correct the loudspeaker-room response. However, when the listener moves in front of the loudspeakers, both the loudspeaker response and room effect change. In order for the best correction to be achieved at all times, adaptive equalization is proposed in this paper. A loudspeaker-correction system using the listener's current location to determine the correction parameters is proposed. The position of the listener's head is located using a depth-sensing camera, and suitable equalizer settings are then selected based on measurements and interpolation. After correcting for the loudspeaker's response at multiple locations and changing the equalization in real time based on the user's location, a loudspeaker response with reduced coloration is achieved compared to no calibration or conventional calibration methods, withthe magnitude-response deviations decreasing from 10.0 to 5.6 dB within the passband of a high-quality loudspeaker. The proposed method can improve the audio monitoring in music studios and other occasions in which a single listener is moving in a restricted space.

Publisher Copyright: © 2022 IEEE. Augmented or mixed reality (AR/MR) is emerging as one of the key technologies in the future of computing. Audio cues are critical for maintaining a high degree of realism, social connection, and spatial awareness for various AR/MR applications, such as education and training, gaming, remote work, and virtual social gatherings to transport the user to an alternate world called the metaverse. Motivated by a wide variety of AR/MR listening experiences delivered over hearables, this article systematically reviews the integration of fundamental and advanced signal processing techniques for AR/MR audio to equip researchers and engineers in the signal processing community for the next wave of AR/MR.

Publisher Copyright: Author Deep neural networks have been successfully used in the task of black-box modeling of analog audio effects such as distortion. Improving the processing speed and memory requirements of the inference step is desirable to allow such models to be used on a wide range of hardware and concurrently with other software. In this paper, we propose a new application of recent advancements in neural network pruning methods to recurrent black-box models of distortion effects using a Long Short-Term Memory architecture. We compare the efficacy of the method on four different datasets; one distortion pedal and three vacuum tube amplifiers. Iterative magnitude pruning allows us to remove over 99% of parameters from some models without a loss of accuracy. We evaluate the real-time performance of the pruned models and find that a 3x-4x speedup can be achieved, compared to an unpruned baseline. We show that training a larger model and then pruning it outperforms an unpruned model of equivalent hidden size. A listening test confirms that pruning does not degrade the perceived sound quality, but may even slightly improve it. The proposed techniques can be used to design computationally efficient deep neural networks for processing the sound of the electric guitar in real time.

The cross-correlation of multichannel reverberation generated using interleaved velvet noise is studied. The interleaved velvet-noise reverberator was proposed recently for synthesizing the late reverb of an acoustic space. In addition to providing a computationally efficient structure and a perceptually smooth response, the interleaving method allows combining its independent branch outputs in different permutations, which are all equally smooth and flutter-free. For instance, a four-branch output can be combined in 4! or 24 ways. Additionally, each branch output set is mixed orthogonally, which increases the number of permutations from M! to M^2!, since sign inversions are taken along. Using specific matrices for this operation, which change the sign of velvet-noise sequences, decreases the correlation of some of the combinations. This paper shows that many selections of permutations offer a set of well decorrelated output channels, which produce a diffuse and colorless sound field, which is validated with spatial variation. The results of this work can be applied in the design of computationally efficient multichannel reverberators.

Flutter echo is a well-known acoustic phenomenon that occurs when sound waves bounce between two parallel reflective surfaces, creating a repetitive sound. In this work, we introduce a method to recreate flutter echo as an audio effect. The proposed algorithm is based on a feedback structure utilizing velvet noise that aims to synthesize the fluttery components of a reference room impulse response presenting flutter echo. Among these, the repetition time defines the length of the delay line in a feedback filter. The specific spectral properties of the flutter are obtained with a bandpass attenuation filter and a ripple filter, which enhances the harmonic behavior of the sound. Additional temporal shaping of a velvet-noise filter, which processes the output of the feedback loop, is performed based on the properties of the reference flutter. The comparison between synthetic and measured flutter echo impulse responses shows good agreement in terms of both the repetition time and reverberation time values.

A computationally efficient octave-band graphic equalizer having a linear-phase response is introduced. The linear-phase graphic equalizer is useful in audio applications in which phase distortion is not tolerated, such as in multichannel equalization, parallel processing, phase compatibility of audio equipment, and crossover network design. The structure is based on the interpolated finite impulse response (IFIR) philosophy. The proposed octave-band graphic equalizer uses one prototype low-pass filter, which is a half-band FIR filter designed using the window method. Stretched versions of the prototype filter and its complementary high-pass filter implement all ten band filters needed. The graphic equalizer is realized in the parallel form, in which the outputs of all band filters, scaled with their individual command gain, are added to compute the equalized output signal. The command gains can be used directly as filter band gains. The number of operations needed per sample is only slightly more than that needed for the graphic equalizer based on minimum-phase recursive filters. A comparison with other implementation approaches demonstrates that the proposed structure requires 99% fewer operations than a high-order FIR filter. The proposed filter uses 39% fewer operations per sample than the fast Fourier transform--based filtering method and causes over 78% less latency.

Publisher Copyright: Author A typical graphic equalizer frequency resolution is one-third octave comprising 31 bands. A previous design based on a least-squares optimization of the band-filter gains with a single second-order section per band has an accuracy of 1 dB. However, the design always uses all the band filters even when a small number of gains is adjusted. This letter proposes a sparse design of a one-third-octave graphic equalizer, where the number of active bands is minimized using orthogonal matching pursuit and linear programming before the least-squares gain optimization. In addition, the bandwidths of the high-frequency band filters are gain dependent in order to optimize their shape relative to an analog prototype. The optimal bandwidth is obtained with linear interpolation during the filter design. The proposed design achieves approximately the same or better accuracy in comparison to the state-of-the-art non-sparse design and can be used to automatically reduce the computational load of equalization when only some bandfilters are active.

Funding Information: This research is part of the activities of the Nordic Sound and Music Computing Network— NordicSMC (NordForsk project no. 86892) and has received funding from the European Union Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 812719. Funding Information: This research is part of the activities of the Nordic Sound and Music Computing Network- NordicSMC (NordForsk project no. 86892) and has received funding from the European Union Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 812719. Publisher Copyright: Copyright: © 2022 Jon Fagerström et al. This paper proposes dark velvet noise (DVN) as an extension of the original velvet noise with a lowpass spectrum. The lowpass spectrum is achieved by allowing each pulse in the sparse sequence to have a randomized pulse width. The cutoff frequency is controlled by the density of the sequence. The modulated pulse-width can be implemented efficiently utilizing a discrete set of recursive running-sum filters, one for each unique pulse width. DVN may be used in reverberation algorithms. Typical room reverberation has a frequency-dependent decay, where the high frequencies decay faster than the low ones. A similar effect is achieved by lowering the density and increasing the pulse-width of DVN in time, thereby making the DVN suitable for artificial reverberation.

In our work, we present and study a novel loudspeaker correction system. This correction system uses the location of the user to determine the calibration parameters. By correcting for the loudspeaker’s response at multiple locations and changing the calibration in real-time based on the user’s location, we expect a less colored frequency response compared to no applied calibration and static calibration methods. The developed method, User PositionBased Loudspeaker Correction (UC), produces a flatter frequency response than that of no applied calibration: for example, in one of the measurement conditions the averages of the ranges of the frequency response went from 10.3 dB in the non-corrected setting to 4.7 dB in the UC setting. Further, it is shown to outperform a static method of correcting for the frequency response of each point in space by using calibration derived from measurements from a predetermined listening position. Finally, by interpolating the EQ gains for the calibration from a set of measurements for the suggested correction method, the system’s resolution could be increased with the resulting calibration still outperforming the static correction method.

Tässä artikkelissa esitellään algoritmi, joka tuottaa hienovaraisia muutoksia iskuääniin. Tavoitteena on parantaa sämpläyksen laatua, missä yksittäisen äänitteen peräkkäinen toisto kuulostaa epäaidolta ja toistuvalta. Äänten spektrien eroja tutkittiin kahdessa äänitteessä, joista ensimmäisessä lyötiin toistuvasti virvelirumpua ja toisessa koputettiin ovea. Spektrianalyysia hyödynnettiin algoritmin kalibroimisessa eri äänilähteille. Kehittämämme algoritmi hyödyntää lyhyttä ja harvaa samettikohinasuodinta ja bassohyllykorjainta satunnaisilla parametreilla, ja tuottaa loputtoman määrän uusia realistisia muunnelmia yhdestä äänitteestä. Muokattujen äänten realistisuutta tutkittiin kuuntelukokeen avulla, jossa verrattiin ehdottamaamme menetelmää aiempaan. Tulokset osoittavat esitetyn algoritmin tuottavan vähintään yhtä realistisen lopputuloksen kuin aiempi menetelmä. Ehdottamamme menetelmä on kuitenkin tehokkaampi, koska se käyttää 77% vähemmän laskuoperaatioita. Uusi menetelmä soveltuu videopelien äänitehosteiden ja tietokonemusiikin elävöittämiseen. Non

The possibility to alter a room's acoustic conditions is useful for spaces requiring specific acoustics depending on diverse functions they serve. Such solutions are applied mostly in multipurpose auditoriums and concert halls, as well as in audio research facilities. The variable acoustics laboratory Arni, a facility within the Acoustics Lab of Aalto University in Espoo, is an example of a space where the wall absorption can be altered considerably with the help of specialized wall- and ceiling-mounted panels. The present work shows the results of measurements of over 5000 panel combinations in Arni, showcasing the change in values of the room acoustic parameters, such as reverberation time and clarity, in relation to the variation of the wall absorption. Non

Decomposition of sounds into their sinusoidal, transient, and noise components is an active research topic and a widely-used tool in audio processing. Multiple solutions have been proposed in recent years, using time–frequency representations to identify either horizontal and vertical structures or orientations and anisotropy in the spectrogram of the sound. In this paper, we present SiTraNo: an easy-to-use MATLAB application with a graphic user interface for audio decomposition that enables visualization and access to the sinusoidal, transient, and noise classes, individually. This application allows the user to choose between different well-known separation methods to analyze an input sound file, to instantaneously control and remix its spectral components, and to visually check the quality of the separation, before producing the desired output file. The visualization of common artifacts, such as birdies and dropouts, is demonstrated. This application promotes experimenting with the sound decomposition process by observing the effect of variations for each spectral component on the original soundand by comparing different methods against each other, evaluating the separation quality both audibly and visually. SiTraNo and its source code are available on a companion website and repository.

Virtual analog (VA) modeling using neural networks (NNs) has great potential for rapidly producing high-fidelity models. Recurrent neural networks (RNNs) are especially appealing for VA due to their connection with discrete nodal analysis. Furthermore, VA models based on NNs can be trained efficiently by directly exposing them to the circuit states in a gray-box fashion. However, exposure to ground truth information during training can leave the models susceptible to error accumulation in a free-running mode, also known as “exposure bias” in machine learning literature. This paper presents a unified framework for treating the previously proposed state trajectory network (STN) and gated recurrent unit (GRU) networks as special cases of discrete nodal analysis. We propose a novel circuit state-matching mechanism for the GRU and experimentally compare the previously mentioned networks for their performance in state matching, during training, and in exposure bias, during inference. Experimental results from modeling a diode clipper show that all the tested models exhibit some exposure bias, which can be mitigated by truncated backpropagation through time. Furthermore, the proposed state matching mechanism improves the GRU modeling performance of an overdrive pedal and a phaser pedal, especially in the presence of external modulation, apparent in a phaser circuit.

A filtering algorithm for generating subtle random variations in sampled sounds is proposed. Using only one recording for impact sound effects or drum machine sounds results in unrealistic repetitiveness during consecutive playback. This paper studies spectral variations in repeated knocking sounds and in three drum sounds: a hihat, a snare, and a tomtom. The proposed method uses a short pseudo-random velvet-noise filter and a low-shelf filter to produce timbral variations targeted at appropriate spectral regions, yield- ing potentially an endless number of new realistic versions of a single percussive sampled sound. The realism of the resulting processed sounds is studied in a listening test. The results show that the sound quality obtained with the proposed algorithm is at least as good as that of a previous method while using 77% fewer computational operations. The algorithm is widely applicable to computer-generated music and game audio.

A virtual bass system creates an impression of bass perception in sound systems with weak low-frequency reproduction, which is typical of small loudspeakers. Virtual bass systems extend the bandwidth of the low-frequency audio content using either a nonlinear function or a phase vocoder, and add the processed signal to the reproduced sound. Hybrid systems separate transients and steady-state sounds, which are processed separately. It is still challenging to reach a good sound quality using a virtual bass system. This paper proposes a novel method, which separates the tonal, transient, and noisy parts of the audio signal in a fuzzy way, and then processes only the transients and tones. Those upper harmonics, which can be detected above the cutoff frequency, are boosted using timbre-matched weights, but missing upper harmonics are generated to assist the missing fundamental phenomenon. Listening test results show that the proposed algorithm outperforms selected previous methods in terms of perceived bass sound quality. The proposed method can enhance the bass sound perception of small loudspeakers, such as those used in laptop computers and mobile devices.

This paper proposes a grey-box neural network based approach to modelling LFO modulated time-varying effects. The neural network model receives both the unprocessed audio, as well as the LFO signal, as input. This allows complete control over the model's LFO frequency and shape. The neural networks are trained using guitar audio, which has to be processed by the target effect and also annotated with the predicted LFO signal before training. A measurement signal based on regularly spaced chirps was used to accurately predict the LFO signal. The model architecture has been previously shown to be capable of running in real-time on a modern desktop computer, whilst using relatively little processing power. We validate our approach creating models of both a phaser and a flanger effects pedal, and theoretically it can be applied to any LFO modulated time-varying effect. In the best case, an error-to-signal ratio of 1.3\% is achieved when modelling a flanger pedal, and previous work has shown that this corresponds to the model being nearly indistinguishable from the target device.

Reverberation is one of the most important effects used in audio production. Although nowadays numerous real-time implementations of artificial reverberation algorithms are available, many of them depend on a database of recorded or pre-synthesized room impulse responses, which are convolved with the input signal. Implementations that use an algorithmic approach are more flexible but do not let the users have full control over the produced sound, allowing only a few selected parameters to be altered. The real-time implementation of an artificial reverberation synthesizer presented in this study introduces an audio plugin based on a feedback delay network (FDN), which lets the user have full and detailed insight into the produced reverb. It allows for control of reverberation time in ten octave bands, simultaneously allowing adjusting the feedback matrix type and delay-line lengths. The proposed plugin explores various FDN setups, showing that the lowest useful order for high-quality sound is 16, and that in the case of a Householder matrix the implementation strongly affects the resulting reverberation. Experimenting with delay lengths and distribution demonstrates that choosing too wide or too narrow a length range is disadvantageous to the synthesized sound quality. The study also discusses CPU usage for different FDN orders and plugin states.

Reverberation time of a room is the most prominent parameter considered when designing the acoustics of physical spaces. Techniques for predicting reverberation of enclosed spaces started emerging over one hundred years ago. Since then, several formulas to estimate the reverberation time in different room types were proposed. Although validations of those models were conducted in the past, they lack testing in a space with a high granularity of controllable absorptive and reflective conditions. The present study discusses thereverberation time estimation techniques by comparing various formulas. Moreover, the reverberation time measurements in a variable acoustic laboratory for different combinations of reflective and absorptive panels are shown. The values calculated with the presented models are compared with the ones obtained via measurements. The results show that all formulas predict reverberation time values inaccurately, with an average error of 16% or larger. Among the analyzed models, Fitzroy’s formula gives the smallest error.

The need for high-quality time-scale modification of audio is increasing, as media streaming services are providing new related functionalities to their users. The main goal of a time-stretching method is to preserve the pitch and the subjective quality of the different components of the audio signal, namely transients, noise, and tonal components. Many solutions have been proposed throughout the years, with various results depending on the kind of processed audio input. This paper introduces an evaluation method for audio time-scaling algorithms based on a recent fuzzy time-frequency decomposition, which reveals the energy of the tonal, transient, and noise components in the original and stretched sounds. From the energy curves, typical impairments, such as transient smearing and the loss of tonality, can be observed. This analysis approach is compared with the subjective preferences of different techniques. This leads to suggestions for possible improvements of future algorithms. The ultimate goal is having an objective evaluation method which matches the subjective quality assessment.

Wikipedia on nykyään varmin tapa levittää tietoa akustiikasta suomalaisille, koska sivustolla on enemmän lukijoita kuin millään muulla medialla. Suomenkielisessä Wikipediassa on kuitenkin akustiikan alan artikkeleita varsin vähän, tätä kirjoitettaessa vain 45 kappaletta, kun englanniksi vastaavia artikkeleita on moninkertainen määrä. Akustisen Seuran hallitus perusti vuoden 2019 alussa viestintätoimikunnan, jonka tehtävänä on ollut muun muassa suomenkielisten akustiikan Wikipedia-sivujen kehittäminen. Työryhmän tarkoituksena on ollut edistää oikean tiedon ja akustiikan käsitteiden leviämistä suomeksi, sekä mainostaa alaamme. Olemme pyrkineet korjaamaan akustiikan sivuilla esiintyviä virheitä ja lisäämään viitteitä, mutta myös välttämään aiemman materiaalin poistamista. Tämän lisäksi olemme pohtineet, mitkä puuttuvat sivut olisi tärkeintä laatia seuraavaksi. Vaikka Wikipediaa ei yleisesti pidetä täysin luotettavana tietolähteenä, tutkimusten mukaan useimmat internetistä tietoa hakevat käyvät katsomassa, mitä siellä on kirjoitettu heidän etsimästään asiasta. Täten, jos tietoa akustiikasta on saatavilla runsaasti Wikipediassa, voimme olettaa myös koululaisten, nuorten ja kaikkien asiasta kiinnostuneiden löytävän sen. Tässä artikkelissa kerromme Wikipedian roolista tiedonlähteenä, sivujen laatimismahdollisuuksista ja suunnitelmistamme akustiikan alan Wikipedia-sivujen kehittämiseksi. Non

Tässä artikkelissa kuvaillaan auton pakoputkiston suunnitteluohjelma, jolla pakoputkiston ulostuloääntä voidaan simuloida ennen rakentamista. Ohjelman toiminta perustuu aaltojohtomalliin, jossa suoraa putkea mallinnetaan viiveillä ja eri osien vaikutusta suodattimilla. Jokaiselle mallinnetulle osalle on määritelty heijastus- ja läpäisykertoimet molempiin suuntiin sekä osan aiheuttama ekvalisointivaikutus mittauksiin perustuen. Mittaukset perustuivat tasoaalto-oletukseen, ja niitä on tehty sekä laboratoriotiloissa että todellisessa ympäristössä, jolloin esimerkiksi herätesignaaliksi on saatu realistista moottorin ääntä. Joidenkin osien ominaisuudet on parametrisoitu, jolloin niitä vastaavat suodattimet riippuvat käyttäjän asettamasta parametrin arvosta. Parametrisointi perustuu joko prototyyppisuodattimeen, jonka ominaisuuksia muokataan vastaamaan asetettua arvoa, tai täysin alusta alkaen suunniteltaviin suodattimiin. Ohjelma on toteutettu Matlabilla ja sitä käytetään graafisen käyttöliittymän avulla. Ohjelman toiminta on varmistettu sekä yksittäisten osien ominaisuuksia kuvaavien suodattimien kohdalla vertaamalla niitä mittaustuloksiin että ohjelman laskennan kohdalla vertaamalla simuloitua putkistoa laboratoriossa mitattuun putkistoon. Non

Artificial reverberation algorithms generally imitate the frequency-dependent decay of sound in a room quite inaccurately. Previous research suggests that a 5% error in the reverberation time (T60) can be audible. In this work, we propose to use an accurate graphic equalizer as the attenuation filter in a Feedback Delay Network reverberator. We use a modified octave graphic equalizer with a cascade structure and insert a high-shelf filter to control the gain at the high end of the audio range. One such equalizer is placed at the end of each delay line of the Feedback Delay Network. The gains of the equalizer are optimized using a new weighting function that acknowledges nonlinear error propagation from filter magnitude response to reverberation time values. Our experiments show that in real-world cases, the target T60 curve can be reproduced in a perceptually accurate manner at standard octave center frequencies. However, for an extreme test case in which the T60 varies dramatically between neighboring octave bands, the error still exceeds the limit of the just noticeable difference but is smaller than that obtained with previous methods. This work leads to more realistic artificial reverberation.

This paper proposes to speed up the design of a third-order graphic equalizer by training a neural network to imitate its gain optimization. Instead of using the neural network to learn to design the graphic equalizer by optimizing its magnitude response, we present the network only with example command gains and the corresponding optimized gains, which are obtained with a previously proposed least-squares-based method. We presented this idea recently for the octave graphic equalizer with 10 band filters and extend it here to the third-octave case. Instead of a network with a single hidden layer, which we previously used, this task appears to require two hidden layers. This paper shows that good results can be reached with a neural network having 62 and 31 units in the first and the second hidden layer, respectively. After the training, the resulting network can quickly and accurately design a third-order graphic equalizer with a maximum error of 1.2 dB. The computing of the filter gains is over 350 times fasterwith the neural network than with the original optimization method. The method is easy to apply, and may thus lead to widespread use of accurate digital graphic equalizers.

An adaptive real-time filtering technique for separating music and ambient noise signals in the ear canal of a headset user is proposed. The system has been tested with a dummy head under laboratory conditions. This paper compares the responses given by the real-time system with those obtained with standard laboratory measurements. Both the headphone response estimate and the noise level measurements remain highly accurate even at a high ambient noise level of 86 dBSPL inside the blocked ear canal. An efficient multirate version of the method is proposed for cases, where the ambient noise is dominated by low frequencies. The method has several useful applications for music listening in noise, including adaptive headphone target response equalization and unmasking of music.

Experimental research into the fundamental acoustic aspects of musical instruments and other sound generating devices is an important part of the history of musical acoustics and of physics in general. This paper presented experimental proof of dispersive wave propagation on metal guitar strings. The high resolution experimental data of string displacement are gathered using video-kymographic high-speed imaging of the vibrating string. The experimental data are indirectly compared against a dispersive Euler-Bernoulli type model described by a PDE. In order to detect the minor wave features associated with the dispersion and distinguish them from other effects present, such as frequency-dependent dissipation, a second model lacking the dispersive (stiffness) term is used. Unsurprisingly, the dispersive effects are shown to be minor but definitively present. The results and methods presented here in general should find application in string instrument acoustics.

The need for loudness compensation is a well known fact arising from the nonlinear behavior of human sound perception. Music and other sounds are mixed and mastered at a certain loudness level, usually louder than the level at which they are commonly played. This implies a change in the perceived spectral balance of the sound, which is largest in the low-frequency range. As the volume setting in music playing is decreased, a loudness compensation filter can be used to boost the bass appropriately, so that the low frequencies are still heard well and the perceived spectral balance is preserved. The present paper proposes a loudness compensation function derived from the standard equal-loudness-level contours and its implementation via a digital first-order shelving filter. Results of a formal listening test validate the accuracy of the proposed method.

This paper studies deep neural networks for modeling of audio distortion circuits. The selected approach is black-box modeling, which estimates model parameters based on the measured input and output signals of the device. Three common audio distortion pedals having a different circuit configuration and their own distinctive sonic character have been chosen for this study: the Ibanez Tube Screamer, the Boss DS-1, and the Electro-Harmonix Big Muff Pi. A feedforward deep neural network, which is a variant of the WaveNet architecture, is proposed for modeling these devices. The size of the receptive field of the neural network is selected based on the measured impulse-response length of the circuits. A real-time implementation of the deep neural network is presented, and it is shown that the trained models can be run in real time on a modern desktop computer. Furthermore, it is shown that three minutes of audio is a sufficient amount of data for training the models. The deep neural network studied in this work is useful for real-time virtual analog modeling of nonlinear audio circuits.

The tuning of a piano is a complicated and time-consuming process, which is usually left for a professional tuner. To make the process faster and non-dependent on the skills of a professional tuner, a semi-automatic piano tuning system is developed. The aim of the system is to help a non-professional person to tune a grand piano with the help of a computer and a motorized tuning machine. The system composes of an aluminum frame, a stepper motor, an Arduino processor, a microphone, and a laptop computer. The stepper motor changes the tuning of the piano strings by turning the pins connected to them whereas the aluminum frame holds the motor in place. The Arduino controls the motor. The microphone and the computer are used as a part of a closed loop control system, which is used to tune the strings automatically. The control system tunes the strings by minimizing the difference between the current and optimal fundamental frequency. The current fundamental frequency is obtained with an inharmonicity coefficient estimation algorithm, and the optimal fundamental frequency is calculated with a novel tuning process, called the Connected Reference Interval (CRI) tuning. With the CRI process, a tuning close to that of a professional tuner is achieved with a deviation of 2.5 cents (RMS) between the keys A0 and G5 and 8.1 cents (RMS) between G#5 and C8, where the tuner’s results are not very consistent.

A virtual tube delay effect based on the real-time simulation of acoustic wave propagation in a garden hose is presented. The paper describes the acoustic measurements conducted and the analysis of the sound propagation in long narrow tubes. The obtained impulse responses are used to design delay lines and digital filters, which simulate the propagation delay, losses, and reflections from the end of the tube which may be open, closed, or acoustically attenuated. A study on the reflection caused by a finite-length tube is described. The resulting system consists of a digital waveguide model and produces delay effects having a realistic low-pass filtering. A stereo delay effect plugin in PURE DATA has been implemented and it is described here.

The impulse response of a generalized two-way loudspeaker is modeled and is delay equalized using digital filters. The dominant features of a loudspeaker are low and high corner roll-off characteristics and the behavior at the crossover points. The proposed model characterizes also the main effects of the mass-compliance resonant system. The impulse response, its logarithm and spectrogram, and the magnitude and group delay responses are visualized and compared with those measured from a two-way loudspeaker. The model explains the typical group-delay variations and magnitude-response deviations from a flat response in the passband. The group-delay equalization of the loudspeaker is demonstrated in two different methods. The first method, the time-alignment of the tweeter and woofer elements using a bulk delay, is shown to cause ripple in the magnitude response. The second method, which flattens the group delay of the speaker model in the whole audio range, leads to preringing in the impulse response.

Many of the dynamic range compressor (DRC) designs that are deployed in the marketplace today are constrained to operate in the time-domain; therefore, they offer only temporally dependent control of the amplitude envelope of a signal. Designs that offer an element of frequency dependency, are often restricted to perform specific tasks intended by the developer. Therefore, in order to realise a more flexible DRC implementation, this paper proposes a generalised time-frequency domain design that accommodates both temporally-dependent and frequency-dependent dynamic range control; for which an FFT-based implementation is also presented. Examples given in this paper reveal how the design can be tailored to perform a variety of tasks, using simple parameter manipulation; such as frequency-depended ducking for automatic-mixing purposes and high-resolution multi-band compression.

The use of the bandlimited ramp (BLAMP) function as an antialiasing tool for audio signals with sharp corners is presented. Discontinuities in the waveform of a signal or its derivatives require infinite bandwidth and are major sources of aliasing in the digital domain. A polynomial correction function is modeled after the ideal BLAMP function. This correction function can be used to treat aliasing caused by sharp edges or corners which translate into discontinuities in the first derivative of a signal. Four examples of cases where these discontinuities appear are discussed: synthesis of triangular waveforms, hard clipping, and half-wave and fullwave rectification. Results obtained show that the BLAMP function is a more efficient tool for alias reduction than oversampling.The polynomial BLAMP can reduce the level of aliasing components by up to 50 dB and improve the overall signal-to-noise ratio by about 20 dB. The proposed method can be incorporated into virtual analog models of musical systems.

The multiphonic playing technique is used in many different musical instruments. It causes one or more partials to be heard alongside the fundamental. In this study, multiphonics on a grand piano were analyzed. For this instrument, the multiphonic technique consists of using a plectrum to slightly press the piano string at a predetermined point in order to rise up the desired partials. The location of the plectrum along the string determines which partials are damped and which are preserved. The partials that have a node at the plectrum position are more pronounced in the sound. For an artistic use of this technique, the purpose is to obtain a piano sound that could be perceived as different tones sounding together, therefore the plectrum position is adjusted so as to obtain sounds composed by many partials. In the experiments, a high-speed line-scan camera was used to detect the motion of the piano string and audio recordings were also obtained for comparison. The camera was equipped with an optical tube extender for better magnification for the images to be recorded. The resulting camera output images were processed, converted into numerical data, and analyzed in the frequency domain. The audio and camera recorded waveforms are presented for comparison, along with their spectrograms. The camera signal is cleaner and less prone to noise than the audio recording. We have observed that using the multiphonics on the grand piano causes the damping of many of the original partials present on an open string, i.e., allowing only a selected few to sound. It has been noticed that even the selected partials in the multiphonics were damped, resulting in softer sounds than the open string.

An efficient signal processing algorithm for generating a sawtooth waveform is proposed. The algorithm improves the trivial waveform sampling method, which suffers from low sound quality due to aliasing. The basic version of the new algorithm differentiates a piecewise parabolic waveform. Another version of the algorithm oversamples and decimates the parabolic wave with a simple filter prior to differentiation. The two algorithm variants improve the signal-to-noise ratio (SNR) over the trivial method by 10 and 15 dB, respectively. A perceptually weighted SNR suggests a larger subjective improvement. The proposed methods are applicable in a digital signal processor (DSP) implementation of subtractive sound synthesis.