[D] What is the difference between Feature Vectors and Embeddings?

I'm working on a user authentication project using **voice** i.e, **voice authentication.** I was researching on what are the different aspects of a given audio/speech which I can make use of to identify a particular person, one of the most commonly used things are the [MFCC](https://www.kaggle.com/code/ilyamich/mfcc-implementation-and-tutorial) features, which are extracted using any standard audio processing library like Librosa.

Now, in recent times we have Embeddings which essential capture the information in the form of vectors, it could be audio, video, …

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