This article presents ethnographic research in the field of algorithmic speech synthesis, conducted in universities in Italy and Germany and in a speech synthesis company. The methodology integrates ethnography, software studies and media archaeology in order to account for the complex socio-technical network of algorithmic systems. Fieldwork included interviews with programmers as well as the examination of speech synthesis algorithms at work. Following analysis of the empirical research, the study discusses epistemological and socio-cultural aspects of data assemblages, focusing on changes in programming practices related to deep learning, a technology that bypasses domain-knowledge and human models of speech to refer directly to the observation of examples. Highlighting the tension between technical operations and social representations of these operations, the paper suggests that the sense-making of algorithms is not to be found in automation, but in the shift in programmers’ position and in the associated subjectivation processes.

"Where is the voice of the machine?". An ethnography of artificial voice socio-technical networks

Domenico Napolitano
2020-01-01

Abstract

This article presents ethnographic research in the field of algorithmic speech synthesis, conducted in universities in Italy and Germany and in a speech synthesis company. The methodology integrates ethnography, software studies and media archaeology in order to account for the complex socio-technical network of algorithmic systems. Fieldwork included interviews with programmers as well as the examination of speech synthesis algorithms at work. Following analysis of the empirical research, the study discusses epistemological and socio-cultural aspects of data assemblages, focusing on changes in programming practices related to deep learning, a technology that bypasses domain-knowledge and human models of speech to refer directly to the observation of examples. Highlighting the tension between technical operations and social representations of these operations, the paper suggests that the sense-making of algorithms is not to be found in automation, but in the shift in programmers’ position and in the associated subjectivation processes.
2020
algorithmic systems; speech synthesis; deep learning; data assemblage; ethnography of programmers.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12570/20251
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact