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Found 7 papers, 0 papers with code
Contextual Density Ratio for Language Model Biasing of Sequence to Sequence ASR Systems
In this work, we propose a contextual density ratio approach for both training a contextual aware E2E model and adapting the language model to named entities.
Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation
Transformer-based models have demonstrated excellent capabilities of capturing patterns and structures in natural language generation and achieved state-of-the-art results in many tasks.
Generating Medical Reports from Patient-Doctor Conversations Using Sequence-to-Sequence Models
We discuss automatic creation of medical reports from ASR-generated patient-doctor conversational transcripts using an end-to-end neural summarization approach.
DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning
We find that DeepAAA exceeds literature-reported performance of radiologists on incidental AAA detection.
Scalable Wide and Deep Learning for Computer Assisted Coding
In recent years the use of electronic medical records has accelerated resulting in large volumes of medical data when a patient visits a healthcare facility.
