Abstract: A method includes receiving a training dataset that includes one or more spoken training utterances for training an automatic speech recognition (ASR) model. Each spoken training utterance in the training dataset paired with a corresponding transcription and a corresponding target sequence of auxiliary tokens. For each spoken training utterance, the method includes generating a speech recognition hypothesis for a corresponding spoken training utterance, determining a speech recognition loss based on the speech recognition hypothesis and the corresponding transcription, generating a predicted auxiliary token for the corresponding spoken training utterance, and determining an auxiliary task loss based on the predicted auxiliary token and the corresponding target sequence of auxiliary tokens. The method also includes the ASR model jointly on the speech recognition loss and the auxiliary task loss determined for each spoken training utterance.

Abstract: A mobile custom-made hand-held chemical detection device interfacing with a smart device. The device includes at least one sensor, a microcontroller, and a Bluetooth module. The at least one sensor detects an associated chemical and generates information in response thereto so as to form chemical detection information. The microcomputer is operatively connected to the at least one sensor and processes the chemical detection information therefrom so as to form processed chemical detection information. The Bluetooth module is operatively connected to the microcontroller and the smart device, and communicates the processed chemical detection information from the microcontroller to the smart device for interpretation.