How DFSMN Cuts Speech Synthesis Model Size by 75% While Quadrupling Speed

This paper introduces a Deep Feedforward Sequential Memory Network (DFSMN) for statistical parametric speech synthesis that matches BLSTM quality with only a quarter of the model size and four times faster inference, making it ideal for memory‑constrained, real‑time IoT devices.

DFSMNDeep LearningIoT devices

0 likes · 10 min read

How DFSMN Cuts Speech Synthesis Model Size by 75% While Quadrupling Speed