Generation of dynamic, scalable multi-species bird soundscapes remains a significant challenge in computer music and algorithmic sound design. Birdsongs involve rapid frequency-modulated chirps, complex amplitude envelopes, distinctive acoustic patterns, overlapping calls, and dynamic inter-bird interactions, all of which require precise temporal and spatial control in 3D environments. Existing approaches, whether Digital Signal Processing (DSP)-based or data-driven, typically focus only on single species modeling, static call structures, or synthesis directly from recordings, and often suffer from noise, limited flexibility, or large data needs. To address these challenges, we present a novel, fully algorithm-driven framework that generates dynamic multi-species bird soundscapes using DSP-based chirp generation and 3D spatialization, without relying on recordings or training data. Our approach simulates multiple independently-moving birds per species along different moving 3D trajectories, supporting controllable chirp sequences, overlapping choruses, and realistic 3D motion in scalable soundscapes while preserving species-specific acoustic patterns. A visualization interface provides bird trajectories, spectrograms, activity timelines, and sound waves for analytical and creative purposes. Both visual and audio evaluations demonstrate the ability of the system to generate dense, immersive, and ecologically inspired soundscapes, highlighting its potential for computer music, interactive virtual environments, and computational bioacoustics research.

翻译：动态、可扩展的多物种鸟类声景生成在计算机音乐与算法声音设计中仍是一项重大挑战。鸟类鸣叫涉及快速频率调制啁啾、复杂振幅包络、独特的声学模式、重叠的鸣叫以及动态的鸟间交互，所有这些在三维环境中均需要精确的时空控制。现有方法，无论是基于数字信号处理（DSP）还是数据驱动，通常仅关注单一物种建模、静态鸣叫结构或直接从录音合成，且常受噪声干扰、灵活性有限或数据需求量大等问题困扰。为应对这些挑战，我们提出了一种新颖的、完全由算法驱动的框架，该框架利用基于DSP的啁啾生成与三维空间化技术生成动态多物种鸟类声景，无需依赖录音或训练数据。我们的方法模拟了每个物种中多个独立移动的鸟类沿不同三维运动轨迹的行为，支持可控的啁啾序列、重叠的合唱以及可扩展声景中真实的三维运动，同时保留物种特有的声学模式。可视化界面提供了鸟类轨迹、频谱图、活动时间线与声波图，以支持分析与创作目的。视觉与听觉评估均表明，该系统能够生成密集、沉浸且生态启发的声景，凸显了其在计算机音乐、交互式虚拟环境及计算生物声学研究中的潜力。