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. |
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