Content Comparison

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Extensions for Dialogue Patterns

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• Refine the responses of your agent: An easy way to make your agent’s responses more interesting is to make sure you add a lot of variety and choice in your agent’s responses. In the assignment instructions, we already suggested that you can use any tool that you can think of to generate more example phrases for your agent that you can add to the responses.pl file. A more challenging thing to do is to contextualize your agent’s responses (they may still sound quite generic or repetitive, making your agent sound even more robotic than it already does). But if not, or you did so only for some contexts, you might want to think about how you can further contextualize and refine your agent responses at various places during a conversation. In principle, agents should, for example, have helpful recovery prompts for each step of the dialog. Here are some useful pointers/ideas:

  • Check out this and other Best practices for repair suggested by Google.

  • More specific feedback: rather than stating misunderstanding, the agent could provide more information on what aspect of the user utterance it did not understand, or provide pointers to what the user can say at that point in the conversation.

  • Suggest alternatives: A breakdown may be due to the fact that a user does not know how to continue the conversation. In that case, the agent could suggest one or more ways to continue.

• Repair: Allow for user-initiated repair: It can happen that a user initiates repair (e.g, “I don’t understand that”, “what do you mean by ‘X’?”). Add a capability that enables the agent to know how to respond to such a user move. That is, make the agent understand such user-initiated repair, and respond with an appropriate explanation to address the user’s move.

• Small talk capabilities related to the recipe domain: small talk can make the agent more engaging for a user. It would require you to think of small talk patterns, either initiated by the user or by the agent, that can be naturally integrated at some point in the recipe recommendation conversation. You would need one or more new intents, patterns, and responses.

• Ask to restart at any point in time: you would need to add a pattern and intents.

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Extensions for Recipe Filtering and Recipe Capabilities

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• Add more types of recipe requests: Add a new filter by adding logic to the recipe_selection.pl file and entity to filter recipes in a new way. An easy one is adding a filter for other recipe attributes present in recipe_database.pl And there are many more you can come up with yourselves.

• Check if the user has all the ingredients: before confirming the recipe, your agent could ask a user if they can check they have all ingredients that the recipe requires. This would require a new pattern, and intents, and perhaps new visuals.

• Read out steps

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extensions to intent and slot classifier - hyperparameter tuning. training augmentation, model augmentation

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