隨著人工智慧聊天機器人逐漸融入日常生活，使用者不僅將其視為資訊提供工具，也開始期待其在互動中提供情緒支持。本研究旨在探討聊天機器人之語音性別（男性、女性與中性／無性別）如何影響使用者對其情緒支持程度的知覺，並進一步檢驗使用者性別是否在其中扮演調節角色。
本研究以媒體等同理論（Media Equation Theory）、電腦為社會行動者典範（Computers as Social Actors, CASA）以及刻板印象內容模型（Stereotype Content Model, SCM）為理論基礎，分析不同性別與性別中立的語音線索如何形塑人機互動中的情緒反應。研究採用實驗設計，讓受試者分別與具備不同語音性別的聊天機器人互動，並評估其所感知的情緒支持程度。
研究結果顯示，聊天機器人語音性別對知覺情緒支持具有顯著影響，其中中性語音條件獲得最高的情緒支持評價；然而，使用者性別並未對此關係產生顯著的調節效果。整體而言，本研究結果指出，性別中立的語音設計可能有助於提升使用者與聊天機器人之間的情緒連結，並為未來發展更具包容性與情緒支持功能的人工智慧系統提供實務與設計上的啟示。

With the increasing integration of AI chatbots into daily life, users rely on them not only for information but also for emotional support. This study examines how chatbot voice gender (male, female, and unisex) influences users perceived emotional support and whether user gender moderates this relationship. Drawing on Media Equation Theory, the Computers as Social Actors (CASA) paradigm, and the Stereotype Content Model (SCM), this research investigates how gendered and gender-neutral voice cues shape emotional responses in human–AI interaction. An experimental design was used in which participants interacted with chatbots with different voice genders and then evaluated their perceived emotional support. The results revealed a significant main effect of chatbot voice gender. The unisex voice condition received the highest perceived emotional support, while user gender did not significantly moderate this effect. These findings suggest that gender-neutral voice designs may enhance users’ emotional connection with AI chatbots and provide important implications for the development of more inclusive and emotionally supportive AI systems

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