Identifying speakers with voice recognition

Next to speech recognition, there is we can do with sound fragments. While speech recognition focuses on converting speech (spoken words) to digital data, we can also use fragments to identify the person who is speaking. This is also known as voice recognition. Every individual has different characteristics when speaking, caused by differences in anatomy and behavioral patterns. Speaker verification and speaker identification are getting more attention in this digital age. For example, a home digital assistant can automatically detect which person is speaking.

In the following recipe, we'll be using the same data as in the previous recipe, where we implemented a speech recognition pipeline. However, this time, we will be classifying the speakers of the spoken numbers. 

How to do it...

1. In this recipe, we start by importing all libraries:

import glob
import numpy as np
import random
import librosa
from sklearn.model_selection import train_test_split...