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arXiv · 2310.12599

On Feature Importance and Interpretability of Speaker Representations

Frederik Rautenberg·Michael Kuhlmann·Jana Wiechmann·Fritz Seebauer·Petra Wagner·Reinhold Haeb-Umbach
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Abstract

Unsupervised speech disentanglement aims at separating fast varying from slowly varying components of a speech signal. In this contribution, we take a closer look at the embedding vector representing the slowly varying signal components, commonly named the speaker embedding vector. We ask, which properties of a speaker's voice are captured and investigate to which extent do individual embedding vector components sign responsible for them, using the concept of Shapley values. Our findings show that certain speaker-specific acoustic-phonetic properties can be fairly well predicted from the speaker embedding, while the investigated more abstract voice quality features cannot.

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Frederik Rautenberg, Michael Kuhlmann, Jana Wiechmann, Fritz Seebauer, Petra Wagner, Reinhold Haeb-Umbach. 2023-10-19. On Feature Importance and Interpretability of Speaker Representations. https://arxiv.org/abs/2310.12599

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