How should the ML specialist fix the problem?
Add the unrecognized words in the enumeration values list as new values in the slot type.
Create a new custom slot type, add the unrecognized words to this slot type as enumeration values, and use this slot type for the slot.
Use the AMAZON.SearchQuery built-in slot types for custom searches in the database.
Add the unrecognized words as synonyms in the custom slot type.
Explanations:
Adding the unrecognized words to the enumeration values list of the existing custom slot type would not help since it would still require modifying the current slot type to accommodate all variations of the category. This is not a scalable solution for handling dynamic or new terms.
Creating a new custom slot type for the unrecognized words and adding them as enumeration values would require changing the current slot type and is not an ideal solution as it adds complexity without leveraging the existing configuration.
The AMAZON.SearchQuery built-in slot type is intended for structured search-related queries, not for defining specific categories like “comedy” or “adventure.” It wouldn’t help to address the issue of category recognition in this context.
Adding the unrecognized words as synonyms in the custom slot type allows Amazon Lex to understand variations of the category term (e.g., “funny,” “humor”) without changing the Lambda function or the DynamoDB data. Synonyms are an effective way to expand the recognition of spoken words while keeping the existing configuration intact.
I deduce that the answer is:
Add the unrecognized words as synonyms in the custom slot type.
I measure that the answer is:
Add the unrecognized words as synonyms in the custom slot type.