Mixture-of-Experts speaker recognition system using ECAPA-TDNN experts with dynamic routing via gating network. Raw audio is transformed to Mel-spectrograms and fed to a CNN-based gating network that learns expert weights, while parallel ECAPA-TDNN experts extract speaker embeddings. Weighted feature aggregation combines expert outputs, normalized to speaker embedding vectors, then classified via AAMSoftmax or ArcFace loss. This MoE approach improves speaker verification accuracy by routing different acoustic patterns to specialized experts, enabling better generalization across diverse speaker populations. Fork and customize this architecture on Diagrams.so to experiment with expert counts, gating mechanisms, or loss functions for your speaker recognition pipeline.