Model Review

45 mins + discussion

This consists of a detailed review of the current model peformance by the HumanFirst team against the loaded data with recommendations to improve.

Generally covering for an NLU system recommendations for

• Subdividing overly greedy intents
• Strengthening weak intents
• Highlighting key intents to disambiguate with example problematic utterances
• Highlighting key intents to merge with example overlapping concepts
• Fixing entity labelling to reduce matching failures
• Reducing clashing entity concepts in labelling
• Specific NLU tuning for labelling based on native eval
• Handling of mistranscriptions and mistyping