A contextual speech recognition method that combines list-, phrase-, and token-level relevance scores and then filters the personal word list improves F1 on varying-length biasing lists relative to three baselines.
Attention-based models for speech recognition,
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Enhancing the Robustness of Contextual ASR to Varying Biasing Information Volumes Through Purified Semantic Correlation Joint Modeling
A contextual speech recognition method that combines list-, phrase-, and token-level relevance scores and then filters the personal word list improves F1 on varying-length biasing lists relative to three baselines.