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Using Deepfake Technologies for Word Emphasis Detection

  • Eran Kaufman
  • , Lee Ad Gottlieb
  • , Dina Mayzlish
  • , Or Tiram
  • , Hila Wiesel
  • , Nofar Yosef

Research output: Contribution to journalConference articlepeer-review

Abstract

In this work, we consider the task of automated emphasis detection for spoken language. This problem is challenging in that emphasis is affected by the particularities of speech of the subject, for example the subject’s accent, dialect or pitch. To address this task, we propose to utilize generative speech deep nets to produce an emphasis-devoid speech sample for the speaker. This requires extracting the text of the spoken voice, and then using a pre-recorded voice sample from the speaker to produce an emphasis-devoid speech for this task. By comparing the generated speech with the spoken voice, we are able to isolate patterns of emphasis which are relatively easy to detect.

Original languageEnglish
JournalPACLIC - Pacific Asia Conference on Language Information and Computation
Issue number2023
StatePublished - 2023
Event37th Pacific Asia Conference on Language, Information and Computation, PACLIC 2023 - Hybrid, Hong Kong, China
Duration: 2 Dec 20234 Dec 2023

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