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Found 4 papers, 0 papers with code
KGLens: A Parameterized Knowledge Graph Solution to Assess What an LLM Does and Doesn't Know
Measuring the alignment between a Knowledge Graph (KG) and Large Language Models (LLMs) is an effective method to assess the factualness and identify the knowledge blind spots of LLMs.
Leveraging Large Language Models for Exploiting ASR Uncertainty
While large language models excel in a variety of natural language processing (NLP) tasks, to perform well on spoken language understanding (SLU) tasks, they must either rely on off-the-shelf automatic speech recognition (ASR) systems for transcription, or be equipped with an in-built speech modality.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Audio-to-Intent Using Acoustic-Textual Subword Representations from End-to-End ASR
Accurate prediction of the user intent to interact with a voice assistant (VA) on a device (e. g. on the phone) is critical for achieving naturalistic, engaging, and privacy-centric interactions with the VA. To this end, we present a novel approach to predict the user's intent (the user speaking to the device or not) directly from acoustic and textual information encoded at subword tokens which are obtained via an end-to-end ASR model.
Complementary Language Model and Parallel Bi-LRNN for False Trigger Mitigation
In this paper, we propose a novel solution to the FTM problem by introducing a parallel ASR decoding process with a special language model trained from "out-of-domain" data sources.
