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

Abstract

A system includes a processor and a memory storing software code and a machine learning (ML) model. The processor executes the software code to receive data including a sequence of acoustic signals or a corresponding spectrogram and an identifier of a source of the acoustic signals, translate, using the ML model, the 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, and obtain, using the identifier of the source, a predetermined word-based description of an acoustic signature of the source. The software code is further executed to determine, using the translated one or more words and the word-based description, whether an anomaly of the source is indicated, and output, when an anomaly is indicated, an alert.