Is it because their listening function reloads in milliseconds or even nanoseconds
Yes, it expects the keyword to start every moment of time and it ignores the rest.
Overall, the algorithm is described here, you can read for details:
Are there examples that transformer have better accuracy than RNN end-to-end model like RNN-transducer for speech recognition?
Can transformer be used for online speech recognition which require low speech-end-to-result latency?
Does transformer have the potential to replace RNN end-to-end models for speech recognition in most cases in the future? This ...
Google has an API you can use. https://cloud.google.com/translate/. Their API can translate audio to text. They also have an API for converting speech to text. The language detection feature should let you detect the language in the resulting text. They have client libraries for the most popular programming languages.
Both of them using the end-to-end approach for speech recognition. However, because of the code complexity in DeepSpeech, you can't tune the model for your work. Kaldi could be configured in a different manner and you have access to the details of the models and indeed it is a modular tool. I think Kaldi could be a better tool academically and also ...