Biometric imaginaries: Formatting voice, body, identity to data

Abstract

This article examines the sociotechnical imaginary within which contemporary biometric listening or VIA (voice identification and analysis) technologies are being developed. Starting from an examination of a key article on Voiceprint identification written in the 1940s, I interrogate the conceptual link between voice, body, and identity, which was central to these early attempts at technologizing voice identification. By surveying patents that delineate systems for voice identification, collection methods for voice data, and voice analysis, I find that the VIA industry is dependent on the conceptual affixion of voice to identity based on a reduction of voice that sees it as a fixed, extractable, and measurable ‘sound object’ located within the body. This informs the thinking of developers in the VIA industry, resulting in a reframing of the technological shortcomings of voice identification under the rubric of big data. Ultimately, this reframing rationalizes the implementation of audio surveillance systems into existing telecommunications infrastructures through which voice data is acquired on a massive scale.

[Retracted] Analysis of Erhu Performance Effect in Public Health Music Works Based on Artificial Intelligence Technology

“…Because the wood used by the luthiers is different, each luthier has his own experience in making the instrument. The timbre of the Erhu instruments is also different, just as no two people in the world have the same voice, which belongs to the personality characteristics of the timbre of the vocalizing body [ 7 , 8 ]. But, we can clearly distinguish between heard voices or Erhu because of voice sound material and other factors, such as voice way of overtones that generate vibration, that is common in tone color, also has the common characteristic.…”

Migration and theDeep Timeof Media Infrastructures

“…As Wendy Chun (2021) unraveled, the history of statistics and artificial intelligence is emerging from eugenics, and its fantasies of locating social features in the body and neutrally measuring it. Contemporary projects (e.g., voice biometrics or automated detection of dialects to assess origin of asylum-seekers; Kang, 2022), are an eerily similar practice of technological knowledge-production at borders today. Finally, the traveling of practices over time not only untangles how migration infrastructure is historically dependent on media infrastructure, but also vice versa: mediated knowledge production at large, such as binary, algorithmic decision making, or biometrics-prevalent more widely in society, far beyond border sites-are developed, experimented with, and emerging from seemingly marginal contexts of migration management and control.…”

“…The beliefs and expectations historically projected on biometrics, such as fingerprint scanning, facial, iris or voice recognition provide an important case in point. "Biometric imaginaries" reflect a deep time of forensic fantasies of exact identification on the basis of eugenic and anthropometric ideals (Kang, 2022). Through time, across various contexts and eras, the body has been approached a site of biometrical technological measurement for the purpose of racial differentiation.…”

“…Fifty years later in the European colonial centers, biometrics were deployed to racially differentiate between desirable and undesirable mobile subjects. In the early 20th century, French authorities invented a "anthropometric nomad passbook," a technology imagined to racially identify growing numbers of undocumented "gypsies" and "nomads" on scientific human measurement of features including skin tones (Kang, 2022). These examples indicate how biometric imaginaries were from the outset based on a default of "infrastructural whiteness" (Pugliese, 2010, p. 56).…”

Ground truth tracings (GTT): On the epistemic limits of machine learning

“…Turow (2021) presents a general survey of what he calls the “voice intelligence” industry and its implications in marketing and advertisement but does not necessarily engage with the underlying technical practices. Kang (2022) analyzes patents of VIA technologies as he examines the biological and social complexities of vocal expression and the ontological tensions that arise as they get reimagined through VIA systems. And finally, Semel (2022) presents findings from her ethnography of a team working on an ML program that analyzes voices of individuals with bipolar disorder to predict whether they’ll have a manic or depressive episode.…”