  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.
