Machine learning model-based acoustic signal-to-text translation

A method for use by a system including a hardware processor and a system memory storing a software code and a machine learning (ML) model, the method comprising:

• receiving, by the software code executed by the hardware processor, a sequence of acoustic signals or a spectrogram corresponding to the sequence of acoustic signals, and data identifying a source of the sequence of acoustic signals;
• translating, by the software code executed by the hardware processor and using the ML model, the sequence of acoustic signals or the spectrogram to one or more words each describing a respective acoustic signal pattern included in the sequence of acoustic signals or represented in the spectrogram;
• obtaining, by the software code executed by the hardware processor and using the identifier of the source, a predetermined word-based description of an acoustic signature of the source;
• determining, by the software code executed by the hardware processor and using the translated one or more words and the word-based description, whether an anomaly of the source is indicated;
• and
• outputting, by the software code executed by the hardware processor when the anomaly is indicated, an alert.