50 years of signal processing at ISSCC

Thon, L.E.

doi:10.1109/isscc.2003.1264034

Cited by 3 publications

(3 citation statements)

References 27 publications

(19 reference statements)

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“…Digital signal processing (DSP) is the method by which signals, such as sound, that have been encoded into digital form are intentionally manipulated(Thon 2003). 15 Sound projection or 'diffusion' is the active practice, originating with the French acousmatic tradition, of redirecting sound to loudspeakers (Emmerson 2017).…”

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confidence: 99%

Aesthetic and technical strategies for networked music performance

Wilson

2020

AI & Soc

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Networked music is no longer a future genre: the global quarantine event of 2020 launched the concept of performing together over the Internet into the mainstream. While the demand for performing at a distance may be a new imperative, musicians find themselves faced with technological and performative processes that do not appear to be suitable for performing music together online, due particularly to network latency which disrupts the ability for musicians to synchronize. The research presented in this paper investigates and challenges the reasons why networked music is not readily embraced by musicians and describes how that might change, by way of interviews with practitioners and an in-depth review of the technical constraints. Limitations that might cause frustration are in fact shown to have creative strategies that give rise to aesthetic approaches, distinct to the platform. By exploiting the constraints, in tandem with developing technology designed specifically for remote performance, aesthetic implications arise that not only accommodate the inconveniences of latency and acoustic feedback but can help us adapt and transform how we engage in real-time online, towards a future where we can imagine performing together over even more dramatic distances such as high-latency, low-bandwidth locations outside of urban areas—or even over galactic distances.

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Aesthetic and technical strategies for networked music performance

Wilson

2020

AI & Soc

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“…Signal processing is the storage, edition or transmission of a signal, either in analog or digital form [1]. Sound, after the acquisition and transformation of acoustic waves into electrical ones, becomes a signal that can be processed.…”

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confidence: 99%

Analyzing the Influence of Diverse Background Noises on Voice Transmission: A Deep Learning Approach to Noise Suppression

Nogales,

Cayuela,

García-Tejedor

2023

Preprint

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This paper presents an approach to enhancing the clarity and intelligibility of speech in digital communications compromised by various background noises. Utilizing deep learning techniques, specifically a Variational Autoencoder (VAE) with 2D convolutional filters, we aim to suppress background noise in audio signals. Our method focuses on four simulated environmental noise scenarios: storms, wind, traffic, and aircraft. Training dataset has been obtained from public sources (TED-LIUM 3 dataset, which includes audio recordings from the popular TED-TALK series) combining with these background noises. The audio signals were transformed into 2D power spectrograms, upon which our VAE model was trained to filter out the noise and reconstruct clean audio. Our results demonstrate that the model outperforms existing state-of-the-art solutions in noise sup-pression. Although differences in noise types were observed, it was challenging to definitively conclude which background noise most adversely affects speech quality. Results have been assessed with objective methods (mathematical metrics) and subjective (listening to a set of audios by humans). Notably, wind noise showed the smallest deviation between the noisy and cleaned audio, perceived subjectively as the most improved scenario. Future work involves refining the phase calculation of the cleaned audio and creating a more balanced dataset to minimize differences in audio quality across scenarios. Additionally, practical ap-plications of the model in real-time streaming audio are envisaged. This research contributes significantly to the field of audio signal processing by offering a deep learning solution tailored to various noise conditions, enhancing digital communication quality.

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“…Digital signal processing (DSP) is the method by which signals, such as sound, that have been encoded into digital form are intentionally manipulated(Thon, 2003). 17 Sound projection or 'diffusion' is the active practice, originating with the French acousmatic tradition, of redirecting sound to loudspeakers(Emmerson, 2017).…”

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confidence: 99%

The constraints, aesthetic implications, and creative strategies of composing for networked music performance

Wilson¹

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<p>Performing music together over a public network while being located at a distance from each other necessarily means performing under a particular set of technical and performative constraints. These constraints are antithetical to—and make cumbersome—the performance of tightly synchronised music, which traditionally depends on the conditions of transmission stability, ultra-low latency, and shared presence. These conditions are experienced optimally only when musicians perform at the same time and in the same place. Except for specialized private network services, public networks are inherently latent and unstable, which disrupts musicians’ ability to achieve precise vertical synchronisation and create an environment where approaches to music performance and composition must be reconsidered. It is widely considered that these conditions mean that networked music performance is a future genre for when network latencies and throughput improve, or one that is currently reserved for high-end heavily optimised networks afforded by institutions and not individuals, or one that is primarily reserved for improvisatory or aleatoric composition and performance techniques. I disagree that networked music is dependent on access to advanced Internet technologies and suggest that music compositions for networked music performance can be highly successful over regular broadband conditions when the composer considers the limitations as opportunities for new creative strategies and aesthetic approaches. In this exegesis, I outline the constraints that prove that while networked music performance is latent, asynchronous, multi-located, multi-authorial, and hopelessly, intrinsically, and passionately digitally mediated, these constraints provide rich creative opportunities for the composition and performance of synchronised and resonant music. I introduce four aesthetic approaches, which I determine as being critical towards the development of networked music: 1) postvertical harmony, where the asynchronous arrival of signals ruptures the harmonic experience; 2) new timbral fusions created through multi-located resonant sources; 3) a contribution to performative relationships through the generation and transmission of vital information in the musical score and through the development of new technologies for facilitating performer synchronisation; and 4) the post-digital experience, where all digital means of manipulation are permitted and embraced, leading to new ways of listening to and forming reproduced realities. Each of these four aesthetic approaches are considered individually in relation to the core constraints, through discussion of the present-day technical conditions, and how each of these approaches are applied to my musical portfolio through practical illustration.</p>

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50 years of signal processing at ISSCC

Cited by 3 publications

References 27 publications

Aesthetic and technical strategies for networked music performance

Aesthetic and technical strategies for networked music performance

Analyzing the Influence of Diverse Background Noises on Voice Transmission: A Deep Learning Approach to Noise Suppression

The constraints, aesthetic implications, and creative strategies of composing for networked music performance

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