Blockchain Papers

Martin Brennecke, Muriel-Larissa FRANK, Nils MESSERSCHMIDT, Gilbert FRIDGEN

Research on innovation resistance has revealed various barriers to the use of digital technologies. However, these studies are typically constrained to siloed perspectives, which prevent comparisons between digital technologies. Therefore, this paper is an initial attempt to explore barriers to adoption across two digital technologies of recent years: generative artificial intelligence (GAI) and distributed ledger technology (DLT). To critically assess the continued applicability of Innovation Resistance Theory (IRT) in relation to these two digital technologies, we analyze a dataset containing over 38,000 Reddit comments. Notably, we identify functional, psychological, and environmental barriers pertaining to both digital technologies, thus enabling us to propose an extension to IRT. Our insights contribute to a better understanding of the adoption of complex digital technologies by uncovering both unique and shared barriers. Thus, this work goes beyond mere absence of adoption factors and can inform the design of digital technologies and organizational adoption management strategies.

Will Mason

In July 2021, the electronic musician and scholar Holly Herndon launched Holly+, a vocal deep fake modeled on her singing voice. Holly+ is powered by an artificial intelligence engine trained on recordings of Herndon’s voice. Musicians were welcome to use the transformed audio commercially and simply credit Herndon and Holly+. They also could release their work with the official imprimatur of a Decentralized Autonomous Organization (DAO), a Web 3.0 entity tied to the Ethereum blockchain. My paper situates the Holly+ project against the backdrop of intellectual property law in the US, both as it stood in the late 2010s and 2020s and in light of the legacy of legally sanctioned appropriation and extraction of work by Black performers. The DAO framework Holly+ uses is unlikely to gain traction, and Herndon and Mat Dryhurst’s provocative invocation of “identity play” suggests an uneasy relationship to the racialized legacy of mimicry and impersonation in the history of American popular music. But the project stands as an important attempt at creating an artist-driven, grassroots effort at monetizing, authenticating, and protecting the intellectual property of musicians in the era of machine learning.

Mihaela Loredana Gârlea

Based on the graphic novel Dalí's Mustache and Other Colors, published by Polirom in 2020, the article Dalí's Mustache between Color, Word, Image, Non-Fungible Token, and... Sound proposes a reevaluation of the concept of musicological research from a contemporary interdisciplinary perspective, as an authentic act of culture. The 16 paintings imagined by visual artist Felix Aftene, perfectly suited to the equally impressive literary chapters written by Lucian Dan Teodorovici, follow a path marked by metamorphosis, with stops that generate new meanings and senses (video artist Andrei Cozlac, Blockchain consultant Gabi Dumitru), with the final destination being the concert stage in the orchestral suite composed by the young musician Paul Pintilie and premiered at the Classix Festival in 2023 on the stage of the “Vasile Alecsandri” National Theater in Iași, performed by the National Youth Orchestra of Moldova and the “Sonos Alumni” Chamber Orchestra of the Iași University of Arts. The article is conceived along parallel lines/arts, but continuously linked by a common thread: Dalí's moustache, a surrealist universe in which the conventional-unconventional dualism fits perfectly.

Femke A.T. de Vries

The rapid ascent of Non-Fungible Tokens (NFTs) has fundamentally disrupted the art market and the broader visual culture landscape. While much scholarly and popular attention has been focused on their economic impact and speculative nature, this article explores a less examined dimension: the potential of blockchain technology, as manifested in NFTs, to redefine the paradigms of digital heritage preservation. Digital art and born-digital cultural artifacts face an existential threat from technological obsolescence, format degradation, and the inherent fragility of digital media. Traditional preservation institutions, such as museums and archives, have struggled to develop scalable, sustainable models for conserving these ephemeral works. This article argues that NFTs, through their core properties of decentralized ownership verification, immutability of provenance, and programmable permanence, offer a novel, albeit complex, framework for safeguarding our collective digital visual heritage. By analyzing the technical architecture of NFTs, the challenges of preserving the digital asset separate from its token, and the emergent models of decentralized autonomous organizations (DAOs) and community-led preservation, this paper posits that we are witnessing the nascent stages of a new preservation ecology. This study synthesizes literature from digital humanities, media studies, conservation science, and computer science to critically assess both the promises and perils of this convergence. It concludes that while NFTs are not a panacea, they introduce powerful tools that, if ethically and thoughtfully integrated, can significantly bolster the resilience and longevity of digital visual culture for future generations.

Andreea Elena Dragnoiu, Ruxandra F. Olimid

Traditional identity management systems, often centralized, face challenges around privacy, data security, and user control, leaving users vulnerable to data breaches and misuse. This paper explores the potential of using the Arweave network to develop an identity management solution. By harnessing Arweave's permanent storage, our solution offers the users a Self-Sovereign Identity (SSI) framework, that uses Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) to allow individuals and other entities to create, own, and manage their digital identities. Further, the solution integrates privacy-preserving technologies, including zero-knowledge proofs and the BBS(+) signature scheme, enabling selective disclosure. This approach ultimately enhances user privacy and supports compliance with European Union legislation and regulatory standards like the General Data Protection Regulation (GDPR) by design.

Matthew Lovett

Chapter 3 presents an analysis of music in relation to emergent models of intellectual property rights, revenue management and digital governance. Rights and revenue patterns are evolving as music becomes increasingly entangled with song funds and decentralised computer architectures, such as blockchain-based streaming platforms and NFTs (non-fungible tokens). In this context, the chapter charts how recorded music’s current format as an intangible data asset is catalysing change in music production and consumption habits. By examining how emergent technological and financial services are offering new revenue models for music creators, contextualised within a broader conception of market economics and value systems, the chapter further explores the ecological nature of music by reflecting on how distribution and income generation mechanisms not only support musicians’ creative practice, but also inform, and to an extent shape, the nature of that practice.

Ahmed Bouzid, Paolo Narciso, Steve Wood

As we stand on the precipice of a new era, the digital age continues to redefine our lives in ways that were once beyond imagination. One revolutionary concept that has rapidly entered mainstream consciousness is that of non-fungible tokens, or NFTs.

Xize Chen, Xiaoyu Qu, Yufeng Qian, Yiyao Zhang

The purposes are to recognize and classify different music characteristics and strengthen the copyright protection system for original digital music in the big data era. Deep learning (DL) and blockchain technology are applied and researched herein. Based on CNN (Convolutional Neural Network), a music recognition method combined with hashing learning is proposed. The error generated when outputting the binary hash code is considered, and the semantic similarity of the hash code is ensured. Besides, the application of blockchain technology in the current intellectual property protection in original music is discussed. According to digital music property rights protection needs, the system is divided into modules, and its functions are designed. The system ensures its various functions by applying the application protocol designed in the Algor and network. In the experiments, the MagnaTagATune dataset is selected to verify the performance of the proposed CRNNH (Convolutional Recurrent Neural Network Hashing) algorithm. The algorithm shows the best music recognition performance under different bit numbers. When the number of connections is about 100, the QPS value of the blockchain-based music property rights protection system can be stabilized at about 20,000. At any number of threads, the system pressure will increase dramatically with the increase in the number of analog connections. The music recognition algorithm based on DL and hash method discussed is of great significance in improving the classification accuracy of music recognition. The application of blockchain technology in the copyright protection platform of original music works can protect the copyright of digital music and ensure the operation performance of the system.

Ian Rogers, Dave Carter, Benjamin A. Morgan, Anna Edgington

Introduction In a 2019 report for the International Journal of Communication, Baym et al. positioned distributed blockchain ledger technology, and what would subsequently be referred to as Web3, as a convening technology. Riffing off Barnett, a convening technology “initiates and serves as the focus of a conversation that can address issues far beyond what it may ultimately be able to address itself” (403). The case studies for the Baym et al. research—early, aspirant projects applying the blockchain concept to music publishing and distribution—are described in the piece as speculations or provocations concerning music’s commercial and social future. What is convened in this era (pre-2017 blockchain music discourse and practice) is the potential for change: a type of widespread, broadly discussed, reimagination of the 21st-century music industries, productive precisely because near-future applications suggest the realisation of what Baym et al. call dreams. In this article, we aim to examine the Web3 music field as it lies some years later. Taking the latter half of 2021 as our subject, we present a survey of where music then resided within Web3, focussing on how the dreams of Baym et al. have morphed and evolved, and materialised and declined, in the intervening years. By investigating the discourse and functionality of 2021’s current crop of music NFTs—just one thread of music Web3’s far-reaching aspiration, but a potent and accessible manifestation nonetheless—we can make a detailed analysis of concept-led application. Volatility remains throughout the broader sector, and all of the projects listed here could be read as conditionally short-term and untested, but what they represent is a series of clearly evolved case studies of the dream, rich precisely because of what is assumed and disregarded. WTF Is an NFT? Non-fungible tokens inscribe indelible, unique ledger entries on a blockchain, detailing ownership of, or rights associated with, assets that exist off-chain. Many NFTs take the form of an ERC-721 smart-contract that functions as an indivisible token on the Ethereum blockchain. Although all ERC-721 tokens are NFTs, the inverse is not true. Similar standards exist on other blockchains, and bridges allow these tokens to be created on alternative networks such as Polygon, Solana, WAX, Cardano and Tezos. The creation (minting) and transfer of ownership on the Ethereum network—by far the dominant chain—comes with a significant and volatile transaction cost, by way of gas fees. Thus, even a “free” transaction on the main NFT network requires a currency and time investment that far outweighs the everyday routines of fiat exchange. On a technical level, the original proposal for the ERC-721 standard refers to NFTs as deeds intended to represent ownership of digital and physical assets like houses, virtual collectibles, and negative value assets such as loans (Entriken et al.). The details of these assets can be encoded as metadata, such as the name and description of the asset including a URI that typically points to either a file somewhere on the Internet or a file hosted via IPFS, a decentralised peer-to-peer hosting network. As noted in the standard, while the data inscribed on-chain are immutable, the asset being referred to is not. Similarly, while each NFT is unique, multiple NFTs could, in theory, point to a single asset. In this respect ERC-721 tokens are different from cryptocurrencies and other tokens like stable-coins in that their value is often contingent on their accurate and ongoing association with assets outside of the blockchain on which they are traded. Further complicating matters, it is often unclear if and how NFTs confer ownership of digital assets with respect to legislative or common law. NFTs rarely include any information relating to licencing or rights transfer, and high-profile NFTs such as Bored Ape Yacht Club appear to be governed by licencing terms held off-chain (Bored Ape Yacht Club). Finally, while it is possible to inscribe any kind of data, including audio, into an NFT, the ERC-721 standard and the underpinning blockchains were not designed to host multimedia content. At the time of writing, storing even a low-bandwidth stereo audio file on the ethereum network appears cost-prohibitive. This presents a challenge for how music NFTs distinguish themselves in a marketplace dominated by visual works. The following sections of this article are divided into what we consider to be the general use cases for NFTs within music in 2021. We’ve designated three overlapping cases: audience investment, music ownership, and audience and business services. Audience Investment Significant discourse around NFTs focusses on digital collectibles and artwork that are conceptually, but not functionally, unique. Huge amounts of money have changed hands for specific—often celebrity brand-led—creations, resulting in media cycles of hype and derision. The high value of these NFTs has been variously ascribed to their high novelty value, scarcity, the adoption of NFTs as speculative assets by investors, and the lack of regulatory oversight allowing for price inflation via practices such as wash-trading (Madeline; Das et al.; Cong et al.; Le Pennec, Fielder, and Ante; Fazil, Owfi, and Taesiri). We see here the initial traditional split of discourse around cultural activity within a new medium: dual narratives of utopianism and dystopianism. Regardless of the discursive frame, activity has grown steadily since stories reporting the failure of Blockchain to deliver on its hype began appearing in 2017 (Ellul). Early coverage around blockchain, music, and NFTs echoes this capacity to leverage artificial scarcity via the creation of unique digital assets (cf Heap; Tomaino). As NFTs have developed, this discourse has become more nuanced, arguing that creators are now able to exploit both ownership and abundance. However, for the most part, music NFTs have essentially adopted the form of digital artworks and collectibles in editions ranging from 1:1 or 1:1000+. Grimes’s February 2021 Mars NFT pointed to a 32-second rotating animation of a sword-wielding cherubim above the planet Mars, accompanied by a musical cue (Grimes). Mars sold 388 NFTs for a reported fixed price of $7.5k each, grossing $2,910,000 at time of minting. By contrast, electronic artists Steve Aoki and Don Diablo have both released 1:1 NFT editions that have been auctioned via Sotheby’s, Superrare, and Nifty Gateway. Interestingly, these works have been bundled with physical goods; Diablo’s Destination Hexagonia, which sold for 600 Eth or approximately US$1.2 million at the time of sale, proffered ownership of a bespoke one-hour film hosted online, along with “a unique hand-crafted box, which includes a hard drive that contains the only copy of the high-quality file of the film” (Diablo). Aoki’s Hairy was much less elaborate but still promised to provide the winner of the $888,888 auction with a copy of the 35-second video of a fur-covered face shaking in time to downbeat electronica as an Infinite Objects video print (Aoki). In the first half of 2021, similar projects from high-profile artists including Deadmau5, The Weekend, Snoop Dogg, Eminem, Blondie, and 3Lau have generated an extraordinary amount of money leading to a significant, and understandable, appetite from musicians wanting to engage in this marketplace. Many of these artists and the platforms that have enabled their sales have lauded the potential for NFTs to address an alleged poor remuneration of artists from streaming and/or bypassing “industry middlemen” (cf. Sounds.xyz); the millions of dollars generated by sales of these NFTs presents a compelling case for exploring these new markets irrespective of risk and volatility. However, other artists have expressed reservations and/or received pushback on entry into the NFT marketplace due to concerns over the environmental impact of NFTs; volatility; and a perception of NFT markets as Ponzi schemes (Poleg), insecure (Goodin), exploitative (Purtill), or scammy (Dash). As of late 2021, increased reportage began to highlight unauthorised or fraudulent NFT minting (cf. TFL; Stephen), including in music (Newstead). However, the number of contested NFTs remains marginal in comparison to the volume of exchange that occurs in the space daily. OpenSea alone oversaw over US$2.5 billion worth of transactions per month. For the most part, online NFT marketplaces like OpenSea and Solanart oversee the exchange of products on terms not dissimilar to other large online retailers; the space is still resolutely emergent and there is much debate about what products, including recently delisted pro-Nazi and Alt-Right-related NFTs, are socially and commercially acceptable (cf. Pearson; Redman). Further, there are signs this trend may impact on both the willingness and capacity of rightsholders to engage with NFTs, particularly where official offerings are competing with extant fraudulent or illegitimate ones. Despite this, at the time of writing the NFT market as a whole does not appear prone to this type of obstruction. What remains complicated is the contested relationship between NFTs, copyrights, and ownership of the assets they represent. This is further complicated by tension between the claims of blockchain’s independence from existing regulatory structures, and the actual legal recourse available to music rights holders. Music Rights and Ownership Baym et al. note that addressing the problems of rights management and metadata is one of the important discussions around music convened by early blockchain projects. While they posit that “our point is not whether blockchain can or can’t fix the problems the music industries face” (403), for some professionals, the blockchain’s promise of eliminating the need for trust seemed to provide an ideal solution to a widely acknowledged business-to-business problem: one of poor metadata leading

Zachary Catanzaro

No abstract is available for this record.

John Nix

[Associate Editor's note: In the September 2008 edition of Voice Research and Technology, I introduced a topic called Quantifying Tessitura in a Song. It was more of a teaser than a complete work. My good friend John Nix completed a real study, including dosimetry on a singer who performed a Mozart composition (different from Il mio tesoro intanto, which I used for my test case)-Ingo R. Titze.]INTRODUCTIONSelecting appropriate repertoire is a primary responsibility for a singing teacher. Astute repertoire selection can help address the technical and musical development of a singer, as well as advance a singer's career in the case of those who are working professionals. Traditionally, repertoire is assigned on an individual basis by carefully considering the singer's age, gender, technical challenges, personality, musicianship, and developmental level, then cross referencing that singer assessment with an evaluation of the vocal, musical, linguistic, and expressive challenges of potential repertoire.1 A number of print2 and web3 resources exist to assist teachers in choosing potential new literature.In the past, the selection process has depended upon the acquired ability of the singing teacher both to evaluate his or her students and to make judgments about vocal repertoire based upon personal knowledge and close examination of the literature. In recent years, however, the voice range profile (VRP) and voice dosimetry have begun to show promise as objective tools that could assist teachers with the selection process.Several articles have suggested ways in which the VRP could be used or improved upon for determining the voice classification of performers or for guiding repertoire choices. Emerich, Titze, Svec, Popolo, and Logan compared laboratory VRPs for eight professional actors with speech range profiles of the actors during a dramatic scene recorded in a laboratory and on stage in performance.4 At times, the actors exceeded their VRP thresholds when in either of the performance conditions. The study highlighted both the utility of the VRP when comparing laboratory values with actual performance voice usage and the shortcomings of the VRP in predicting what repertoire might exceed a performer's capabilities given the emotional content of live performance. Lamarche, Ternstrom, and Hertegârd also looked at the VRP as compared to the performance of repertoire, combining a commercial VRP program with a response button that subjects pressed during moments of difficult production.5 The subjects, all female professionally trained singers, performed three tasks, including the singing of their best aria, using performance-acceptable quality. Subjects also rated how well the button pressings reflected their experiences and usual vocal challenges; this rating included a viewing of a visual graph of the button responses. The investigators' coupling of objective data from the VRP tasks with (a) the singer's self-assessment captured mid-task and (b) the postperformance evaluation of the data and the responses shows significant promise as a means for enhancing singing teachers' guidance of their students. Lamarche, Ternstrom, and Pabon continued testing improvements of the VRP for singers by examining whether VRPs for singers should be limited to physiological measures (without considering performance quality elements), or whether performance abilities should also be measured in some fashion.6 After testing thirty female subjects, all professionally active singers, they concluded that examining the voice as it is used in performance has clinical importance, and that both types of VRPs should be used for assessing singers. Finally, Herbst, Duus, Jers, and Svec compared the maximum phonation frequency range (MPFR) of amateur choir singers (as gathered during a VRP) with the required pitch range (RPR) for their chosen voice part within a choir, based upon part ranges specified in a commonly used music reference. …

Steven M Boker, Michael J. Wenger

In certain mathematical statistical circles, there appear to linger doubts about the soundness of latent variables, in particular common factors in factor models. In what follows we will show, to the best of our knowledge for the first time, that a common latent factor in a factor model can be conceived of as a genuine scientific construct obeying the usual formal criteria for such constructs. Following the discussion in Simon (1977, ch. 6 .6 ) it will be shown that a common factor in a factor model can be transformed into a network of regres­sion relationships between the manifest (observed) variables. Because this transformation is invertible, we end up with two strictly equiva­lent models; the factor model and a model without the factor. This shows that the latent factor in a factor model serves as a placeholder for a system of relationships between the manifest variables and thus obeys the most stringent criterion for valid scientific constructs (cf. Simon, 1977).In what follows, we present a complete constructive proof that the latent factor in a 1 -factor model can be transformed away, yielding a model composed of a network of regression relationships between the observed variables. Preliminary work in this direction can be found in a recent book by the first author that can be freely downloaded from internet (Molenaar, 2003). Also the paper by Rovine and Molenaar (2005) contains further elaborations. But in this chapter, we for 189 the first time present all steps in the proof in full detail and for the simplest possible situation, a 1 -factor model. Even though we take great care to explain the steps in the proof as clearly as possible, a lot is asked of the reader. We suppose that they have a working knowledge of structural equation model­ing, are acquainted with elementary matrix algebra, and are willing to work through some unfamiliar notions taken from time series anal­ysis. These efforts only can be asked if the returns are irresistible. And in our opinion the results presented in this chapter are quite revolutionary. For the first time a general technique, an invertible transformation, is presented with which one can remove latent vari­ables from a latent variable model without any loss of information. This makes explicit something basic about the scientific nature of la­tent variables: They are real and have solid groundings in the data. It turns out to be a matter of taste whether one wants to enter­tain a latent variable model, or instead, its equivalent representation without latent variables. Of course, latent variable models may be better interpretable (in our opinion, they almost always are) and we certainly do not want to advertise the unconditional use of our trans­formation technique. But a proof that latent variables, in particular common factors, can be reduced to functional relationships between manifest variables shows that these latent variables share all their for­mal and semantic qualities with other respectable scientific constructs like electromagnetic potential, entropy, and so forth. This is not only important from a philosophy of science point of view, but also for discussions about the status of well-known psychometrical constructs like reliability and validity (cf. Borsboom, Mellenbergh, & Heerden, 2003). Another implication of the proof to be given shortly is that all structural equation models can be shown to be nested. This par­ticular implication is not elaborated in this chapter, but details can be found in Rovine and Molenaar (2005) and in Molenaar (2003). To give one particular example, it can be shown that the latent growth curve model is nested under the latent simplex model (contra Rogosa & Willett, 1985; see also Mandys, Dolan, &; Molenaar, 1994). But the harvest is much bigger. If, as will be shown, it is possible to remove the factor from a 1 -factor model, then apparently it is possible to reduce the common latent dimension from one to zero. Because after the removal of the latent common factor (which defines the common one dimension in the initial 1 -factor model), there are no longer any common latent factors in the obtained equivalent model (hence the latent dimension in the latter model is zero). It is shown in Molenaar (2003) that this result holds in general. To illustrate, starting with a standard 2-factor model (where the two factors span up a two-dimensional common latent space), it is possible to transform this model to an equivalent model in which the common latent space is one-dimensional. Finally, the model obtained in the previous step can itself again be transformed into an equivalent model in which the common latent space is absent (zero-dimensional). This, of course, raises urgent questions about the proper definition of the dimension of a common latent space (like in statements such as “this psycho­logical test is indicative of two underlying dimensions”). There are additional important implications, although of a much more theo­retical nature. We mention only the direct relationship of the kind of result that we are about to prove with similar results obtained in mathematical system theory and statistical field theory (both of which are elaborated somewhat further in Molenaar, 2003). We hope and expect that sufficient reasons have been provided to carry on reading this chapter.