MiniMax-Speech: Revolutionizing Zero-Shot Text-to-Speech with Learnable Speaker Encoder and Flow-VAE Technology 1. Core Innovations and Architecture Design 1.1 Architectural Overview MiniMax-Speech leverages an 「autoregressive Transformer architecture」 to achieve breakthroughs in zero-shot voice cloning. Key components include: 「Learnable Speaker Encoder」: Extracts speaker timbre from reference audio without transcriptions (jointly trained end-to-end) 「Flow-VAE Hybrid Model」: Combines variational autoencoder (VAE) and flow models, achieving KL divergence of 0.62 (vs. 0.67 in traditional VAEs) 「Multilingual Support」: 32 languages with Word Error Rate (WER) as low as 0.83 (Chinese) and 1.65 (English) Figure 1: MiniMax-Speech system diagram (Conceptual illustration) 1.2 Technical Breakthroughs (1) Zero-Shot Voice …