Emojis offer an intuitive and affective means of emotional communication in digital environments. However, existing AI-driven music generation systems often rely on text-based inputs, which may be cognitively demanding and less precise in conveying emotions. This study presents EmoGen, an emoji-based interactive application that supports emotional expression in generative music. Users select emojis across five categories: emotion, scene, object, style, and instrument, which are mapped to text prompts for customized music generation with audiovisual feedback. A mixed-method evaluation with eight participants (aged 21–48) was conducted, using the System Usability Scale (SUS) and thematic analysis of interview data. Results showed high emotional alignment between user inputs and generated music (mean = 7.12–7.88/10) and strong usability (SUS = 80.9). Qualitative feedback highlighted use cases such as emotional journaling, event-based music creation, and mood-based self-care. The evaluation results suggest that EmoGen supports active emotional exploration through symbolic musical interaction, externalizing the externalization of emotions into personalized soundscapes. This work demonstrates how intuitive emoji-based interfaces can enhance emotional resonance and contribute to emotional interaction design in generative music systems.