Paraformer (Alibaba FunASR)

Paraformer is a cutting-edge non-autoregressive (NAR) end-to-end automatic speech recognition model developed by Alibaba DAMO Academy. Unlike traditional autoregressive models that generate text token-by-token, Paraformer utilizes a parallel decoding architecture enabled by a Continuous Integrate-and-Fire (CIF) predictor. This technical innovation allows it to achieve inference speeds up to 10x faster than standard Conformer models while maintaining state-of-the-art accuracy, particularly in Mandarin and English contexts. As of 2026, it serves as the core engine within the FunASR framework, supporting complex tasks such as voice activity detection (VAD), punctuation prediction, and speaker diarization within a single pass. Its architecture is specifically optimized for GPU utilization, making it the preferred choice for high-throughput enterprise environments like live broadcast subtitling, call center analytics, and large-scale video indexing. The model is available both as an open-source repository for self-hosting and via Alibaba Cloud's DashScope API for managed scaling.