2 citations · 6 across the 12 of their papers we have counts for
12 papers
Effective internal language model training and fusion for factorized transducer model
Jinxi Guo, Niko Moritz, Yingyi Ma +6
The internal language model (ILM) of the neural transducer has been widely studied. In most prior work, it is mainly used for estimating the ILM score and is subsequently subtracte…
Correction Focused Language Model Training for Speech Recognition
Yingyi Ma, Zhe Liu, Ozlem Kalinli
Language models (LMs) have been commonly adopted to boost the performance of automatic speech recognition (ASR) particularly in domain adaptation tasks. Conventional way of LM trai…
Forgetting Private Textual Sequences in Language Models via Leave-One-Out Ensemble
Zhe Liu, Ozlem Kalinli
Recent research has shown that language models have a tendency to memorize rare or unique token sequences in the training corpus. After deploying a model, practitioners might be as…
Contextual Biasing of Named-Entities with Large Language Models
Chuanneng Sun, Zeeshan Ahmed, Yingyi Ma +4
This paper studies contextual biasing with Large Language Models (LLMs), where during second-pass rescoring additional contextual information is provided to a LLM to boost Automati…
End-to-End Speech Recognition Contextualization with Large Language Models
Egor Lakomkin, Chunyang Wu, Yassir Fathullah +3
In recent years, Large Language Models (LLMs) have garnered significant attention from the research community due to their exceptional performance and generalization capabilities.…
Augmenting text for spoken language understanding with Large Language Models
Roshan Sharma, Suyoun Kim, Daniel Lazar +7
Spoken semantic parsing (SSP) involves generating machine-comprehensible parses from input speech. Training robust models for existing application domains represented in training d…