Algorithmic Ventriloquism: The Contested State of Voice in AI Speech Generators

Abstract

This article explores the vocal human–machine relations embedded in text-to-speech (TTS) generators. Retracing the human sources behind the synthetic speech and tracking the remediation of the voice by the machine-learning algorithm, it argues that artificial intelligence (AI) speaking agents such as Siri and Alexa, as well as other TTS acts such as TikTok’s, are performing algorithmic ventriloquism. Speaking mechanically with the voices of professional voiceover artists, AI speech technologies algorithmically manipulate these voices, thus generating personas that hold an interconnected chain of tensions between the embodied and the virtual, the particular and the general, the human and the non-human, as well as between speech and writing. Algorithmic ventriloquism serves as an analytical framework to tie the techno-vocalic operation of the TTS system with its cultural, economic, philosophical, and sociolinguistic predicaments. The last section discusses the implications of algorithmic ventriloquism beyond the realm of the voice.

The Effectiveness of Pretend Play Method Based on Local Wisdom towards Social Skills of Children

“…Pretend play involves the children to play mock by following an impromptu path where ventriloquism is used to speak objects in life through paralinguistic features such as movement gestures, gazes and sounds. These findings indicated that through ventriloquism action in mock plays, the children learn to engage in the complex meaning of making activities in fun ways, formulating oral characters and building a coherent and systematic storyline that can be identified as early literacy practices (Ramati, 2024). Most of the teachers make pretend play stories with medical themes, but the children are less influential as well as less fantasy and comfortable during the play.…”