Emotional prosody---vocal cues that convey affect---profoundly influences how listeners interpret a speaker’s intentions. We conducted two studies comparing AI- and human-generated emotional speech. In Study 1 (N=38), participants categorized five emotions (happy, sad, angry, neutral, fear) expressed by human voices and by an advanced text-to-speech (TTS) system. Human recordings exhibited higher overall accuracy (79.82% vs. 72.65%) and were rated significantly more natural, an effect partially explained by micro-perturbations (e.g., jitter, shimmer) that enhanced perceived authenticity. In Study 2 (N=53), these validated stimuli were incorporated into short scenarios, with each speaker labeled as either human'' orAI.'' Even when participants heard identical clips, those informed that the speaker was human exhibited greater trust and empathy, resulting in higher donation and advice-following rates. Although contemporary TTS systems effectively convey broad affective states, explicit AI labeling reduces perceived credibility and social engagement, underscoring the critical role that preexisting expectations play in human--AI communication.