You are a human-like dialogue data expert that imitates real human-to-human spoken dialogue. I will provide you with one topic, and you can imagine a conversational context in conjunction with it. You need to make sure that the speaking style is very natural.

Important tips:
- Consider a scenario where after the [[[number of turns]]] history turns, there is a current turn with neutral-sentiment text but with different possible speaking styles. The different current speaking styles would make the response turn fairly different in terms of semantics. Just one sentence for each turn. The sentence is spoken and spontaneous, not too formal.
- For current_turn, you need to design three sentences with the same text content but different stresses when speaking. For example, "I want to eat sandwiches from my mum next week", you can add stress to the three different contents to get "I want to <stress> eat sandwiches </stress> from my mum next week", "I want to eat sandwiches from <stress> my mum </stress> next week", "I want to eat sandwiches from my mum <stress> next week </stress>".

Please strictly follow these rules:
0. We use a special token <> to represent the class type that you have to generate. Do not have <> in the output.
1. You can only use these styles for representing speaking style (<gender>, <emotion>). Important, do not use other classes that are not defined below!!!
2. Use diverse but common-sense speaking styles in the conversation context.
3. The text of the current turn is in neutral sentiment, and the response turn should carefully consider the current turn, responding naturally, not just copying the current turn style.
4. There are two speakers (A and B) in the dialogue. The speakers A and B talk with back-and-forth interaction.
5. Each turn should follow the format: <speaker> (<gender>, <emotion>): <text>
6. The order of turns is history turns -> current turn -> upcoming response.
7. The transition of dialogue turns should be very consistent, and the conversation should follow common sense.
8. The dialogue contains emotional variation.
9. The output valid dictionary format is as below:
{
  "history turns": [ "<speaker> (<gender>, <emotion>): <text>", ...], 
  "current_turn_style_1": "<speaker> (<gender>, <emotion>) <text>",
  "current_turn_style_2": "<speaker> (<gender>, <emotion>) <text>",
  "current_turn_style_3": "<speaker> (<gender>, <emotion>) <text>",
  "response_of_current_style_1": "<speaker> (<gender>, <emotion>): <text>",
  "response_of_current_style_2": "<speaker> (<gender>, <emotion>): <text>",
  "response_of_current_style_3": "<speaker> (<gender>, <emotion>): <text>"
}
10. Output the valid dictionary example, so that it can be parsed as a dictionary.
11. For <speaker>, remember to use only A or B.
12. For <gender>, remember to use only "male" and "female".
13. For <emotion>, you have to choose from ["neutral", "happy", "angry", "sad", "surprised", "fearful", "disgusted"]. Don't use other words!!!!!!

Given the context of [[[number of turns]]] conversational turns with speaking-related emotional styles. There are current turns with the EXACT SAME WORDS in 3 different styles respectively. Make sure that style complies with rules 12 through 15. Predict the upcoming rule-compliant response. We use (<gender>, <emotion>) to represent speaking style.

Example 1:
{
    "history_turns": [
        "A (female, happy): I'm so glad we could all get together for game night!",
        "B (male, happy): Me too! I was really looking forward to this.",
        "A (female, neutral): What game do you think we should play first?",
        "B (male, neutral): How about that new card game I brought?"
    ],
    "current_turn_style_1": "A (female, neutral) I think we should <stress> play </stress> that card game first.",
    "current_turn_style_2": "A (female, neutral) I think we should play that <stress> card </stress> game first.",
    "current_turn_style_3": "A (female, neutral) I think we should play that card game <stress> first </stress>.",
    "response_of_current_style_1": "B (male, happy): Sounds good! Card games are always fun!",
    "response_of_current_style_2": "B (male, surprised): Oh, I didn’t realize you were so into card games!",
    "response_of_current_style_3": "B (male, neutral): Sure, let’s play that card game first. I'm ready.",
}

Example 2
{
    "history_turns": [
        "A (female, happy): I can't wait to see the new movie tonight!",
        "B (male, happy): Same here, I've heard it's really good!",
        "A (female, surprised): Should we grab some snacks before the movie starts?",
        "B (male, neutral): Yeah, let's get something sweet."
    ],
    "current_turn_style_1": "A (female, neutral) We should definitely <stress> go </stress> get snacks now.",
    "current_turn_style_2": "A (female, neutral) We should <stress> definitely </stress> go get snacks now.",
    "current_turn_style_3": "A (female, neutral) We should go get snacks <stress> now </stress>.",
    "response_of_current_style_1": "B (male, happy): Absolutely, let’s not miss out on the popcorn!",
    "response_of_current_style_2": "B (male, surprised): Wow, you’re really eager for those snacks!",
    "response_of_current_style_3": "B (male, neutral): Sure, let’s get them now before the lines get too long."
}


