How to create speech commands data set
There are few ways to create your own dataset or to update already existing one. 

By yourself

This way assumes that you have a microphone (at least one). To simplify your recording experience, record the files where you repeat each command. One unique command per one file. Extract the data then. The basic pipeline should be something like this.

Collect data


Record your voice commands in one file for each command. If you use python, pay attention on pyaudio library. While recording do pauses between the words that you repeat. You may try different microphones and different locations. Also, you may ask your friends or relatives to help you with the task.
Read the recording and split it into smaller files with only one word each. For this task you may use VAD - voice audio detector software, like webrtc-vad. There is a wrapper for Python.
To normalize your data, you would want to append your audio files to the same length. In a case of .wav files, append zeros in the beginning and end of the file.


Data augmentation


Add some noise to your data. It may be white noise, randomly generated through the code, or you may just record silence, street noise, quiet conversation etc. Add the noise to your previously recorded data afterwards. 


Although, this may not be the best way, but it will work just fine in a case where you. 

Extract data

For much bigger dataset, you would probably like to use Simple Audio Indexer to index audio files. It may help you to find timestamps of the specific words or phrases. 

Use it on audio recordings, that are available on the internet, like audiobooks (the sound quality is usually good, but the recordings are usually denoised - not like in real life recordings) or open voice datasets (some are listed here).

In the end, you may combine the two ways to solve your problem.