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 language | English |
|---|---|
| Journal | PACLIC - Pacific Asia Conference on Language Information and Computation |
| Issue number | 2023 |
| State | Published - 2023 |
| Event | 37th Pacific Asia Conference on Language, Information and Computation, PACLIC 2023 - Hybrid, Hong Kong, China Duration: 2 Dec 2023 → 4 Dec 2023 |
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