Downsampling audio files for use in Machine Learning
Resampling of audio is a standard process and there are many implementations available. In Python you can use librosa, or you can write a script that uses ffmpeg or similar.

If you want to reuse an already trained model this is critical, as the neural network will have learned features based on 16kHz input. It might work OK if you re-train the model with your data using 48kHz. It will be slower to train and predict, but performance can be similar.
However your would need to update the audio_sr parameter of the audio feature extraction. Otherwise the length of window in milliseconds would be wrong, probably no longer matching what is typical for speech, resulting in degraded performance.