7 citations · 9 across the 5 of their papers we have counts for
4 papers · 1 filter
Lessons from the Field: An Adaptable Lifecycle Approach to Applied Dialogue Summarization
Kushal Chawla, Chenyang Zhu, Pengshan Cai +9
Summarization of multi-party dialogues is a critical capability in industry, enhancing knowledge transfer and operational effectiveness across many domains. However, automatically…
CUE Vectors: Modular Training of Language Models Conditioned on Diverse Contextual Signals
Scott Novotney, Sreeparna Mukherjee, Zeeshan Ahmed +1
We propose a framework to modularize the training of neural language models that use diverse forms of sentence-external context (including metadata) by eliminating the need to join…
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,…
Improving accuracy of rare words for RNN-Transducer through unigram shallow fusion
Vijay Ravi, Yile Gu, Ankur Gandhe +5
End-to-end automatic speech recognition (ASR) systems, such as recurrent neural network transducer (RNN-T), have become popular, but rare word remains a challenge. In this paper, w…