Abstract: Disclosed are apparatuses, systems, and techniques that may use machine learning for implementing automatic speech recognition (ASR) facilitated with a search for target words. The techniques include applying an ASR model to audio data to generate an ASR output representative of a likelihood that the audio data comprises one or more spoken speech units (SUs), generating, using the ASR output, a first score characterizing a likelihood that the audio data comprises a first word, wherein the first word comprises a dictionary word, generating, using the ASR output, a second score characterizing a likelihood that the audio data comprises a second word, wherein the second word comprises a word of a plurality of target words, wherein the plurality of target words is identified based at least on a context of the audio data, and predicting, using the first score and the second score, a spoken word associated with the audio data.

Abstract: Disclosed are apparatuses, systems, and techniques that implement training and deployment of speech-augmented language models for efficient capturing and processing of speech inputs. The techniques include processing, using a speech model, an audio input in a first language to generate a first portion of an input into a language model (LM). A second portion of the input into the LM includes represents a text context associated with the audio input. The techniques further include receiving, from the LM, an output that includes a speech-to-text conversion of the audio input.