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This paper investigates the application of patent analytics for evaluating technological trends and identifying strategic development directions in the field of audio deepfakes—a rapidly growing segment within generative artificial intelligence (AI). The study examines the integration of synthetic voice technologies into the digital transformation of the retail sector, focusing on their use in customer service automation, personalized marketing, accessibility enhancement, and brand communication. A comprehensive patent landscape covering global trends from 2017 to 2024. The results revealed key patent holders, leading jurisdictions, and high-potential IPC classes related to speech synthesis and detection. The paper also identifies gaps in the competitive landscape and unoccupied market niches. Special attention is given to the ethical and regulatory challenges of deploying audio deepfakes in commercial environments. The findings offer practical recommendations for organizations aiming to develop or protect solutions involving generative AI for speech synthesis and recognition.

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Analysis of the Commercialization Potential of Digital Solutions in the Field of Generative Artificial Intelligence Based on the Patent Landscape

  • 会议论文

  • 发表日期：

    2025年

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  • A. S. Nikolaev,
  • O. A. Kokorina,
  • A. S. Telyatev,
  • A. N. Kirillova,
  • N. D. Seliverstov

摘要

This paper investigates the application of patent analytics for evaluating technological trends and identifying strategic development directions in the field of audio deepfakes—a rapidly growing segment within generative artificial intelligence (AI). The study examines the integration of synthetic voice technologies into the digital transformation of the retail sector, focusing on their use in customer service automation, personalized marketing, accessibility enhancement, and brand communication. A comprehensive patent landscape covering global trends from 2017 to 2024. The results revealed key patent holders, leading jurisdictions, and high-potential IPC classes related to speech synthesis and detection. The paper also identifies gaps in the competitive landscape and unoccupied market niches. Special attention is given to the ethical and regulatory challenges of deploying audio deepfakes in commercial environments. The findings offer practical recommendations for organizations aiming to develop or protect solutions involving generative AI for speech synthesis and recognition.