Generating Synthetic Doctor-Patient Conversations for Long-form Audio Summarization

1. 1Design a synthetic data generation pipeline for long-form audio summarization
2. 2Implement the pipeline for doctor-patient conversations
3. 3Use the generated data for training and evaluating long-context audio reasoning models
4. 4Evaluate the effectiveness of the pipeline in improving model performance

Natural Language Processing (NLP) engineers and researchers on a team can benefit from this pipeline to improve long-context audio reasoning, while data scientists and ML engineers can utilize the generated data for training and evaluation purposes

💡 Synthetic data generation can be used to address the lack of training data and evaluation benchmarks for long-context audio reasoning

💡 Synthetic data generation for long-form audio summarization!