Papers with contextual LM
Attention-based Contextual Language Model Adaptation for Speech Recognition (2021.findings-acl)
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| Challenge: | Existing language models do not incorporate utterance level contextual information . however, for some domains like voice assistants, additional context provides a rich input signal . |
| Approach: | They propose a method for training neural speech recognition models on text and contextual data. |
| Outcome: | The proposed model reduces perplexity by 7.0% relative over a standard LM . it also improves perxicity by 2.8% relative to a state-of-the-art model for contextual LM. |
CUE Vectors: Modular Training of Language Models Conditioned on Diverse Contextual Signals (2022.findings-acl)
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| Challenge: | Using contextual universal embeddings, we train neural language models on one type of contextual data and adapts to novel context types. |
| Approach: | They propose a framework to modularize the training of neural language models that use diverse forms of context by eliminating the need to jointly train context and within-sentence encoders. |
| Outcome: | The proposed framework trains LMs on one type of contextual data and adapts to novel context types. |