53 citations · 151 across the 26 of their papers we have counts for
4 papers · 1 filter
Towards Continual Entity Learning in Language Models for Conversational Agents
Ravi Teja Gadde, Ivan Bulyko
Neural language models (LM) trained on diverse corpora are known to work well on previously seen entities, however, updating these models with dynamically changing entities such as…
Attention-based Contextual Language Model Adaptation for Speech Recognition
Richard Diehl Martinez, Scott Novotney, Ivan Bulyko +3
Language modeling (LM) for automatic speech recognition (ASR) does not usually incorporate utterance level contextual information. For some domains like voice assistants, however,…
Domain-aware Neural Language Models for Speech Recognition
Linda Liu, Yile Gu, Aditya Gourav +5
As voice assistants become more ubiquitous, they are increasingly expected to support and perform well on a wide variety of use-cases across different domains. We present a domain-…
Personalization Strategies for End-to-End Speech Recognition Systems
Aditya Gourav, Linda Liu, Ankur Gandhe +9
The recognition of personalized content, such as contact names, remains a challenging problem for end-to-end speech recognition systems. In this work, we demonstrate how first and…