I won't jump to that conclusion but I'm skeptical. Phrenology seemed like it worked (to some) until real rigor and statistically significant sample sizes put it to rest. I suspect that may happen to facial and voice recognition too - if limited to a small, known group size or heavily controlled circumstances it works well, but the second you apply it to nontrivial real world populations over time it loses most of its predictive power. Obviously even in limited applications the technology is far more useful than phrenology ever was, just going by the number of people using Face ID.
At the end of the day, the predictions facial/voice recognition algorithms make are far more specific and obviously testable than phrenology ever was, but we don't even have conclusive evidence that humans can precisely identify individuals using only sight or sound without a mental context that would approach a general AI. Even parents, for example, can have trouble differentiating identical twins without contextual clues like personality traits, schedule, or preferred fashion.