How Deep‑FSMN and Low Frame Rate Accelerate Speech Recognition

This article introduces the Deep‑FSMN (DFSMN) architecture and its integration with low‑frame‑rate (LFR) processing, showing how the combined LFR‑DFSMN acoustic model achieves higher accuracy, smaller model size, faster training, and lower latency than traditional BLSTM‑based speech recognition systems on both English and Chinese large‑vocabulary tasks.

AIDFSMNacoustic modeling

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How Deep‑FSMN and Low Frame Rate Accelerate Speech Recognition

Alibaba Cloud Developer

Jun 8, 2018 · Artificial Intelligence

How DFSMN Sets a New Record in Speech Recognition Accuracy and Speed

Alibaba's DAMO Academy has open‑sourced the Deep‑Feedforward Sequential Memory Network (DFSMN), a next‑generation speech‑recognition model that achieves a world‑record 96.04% accuracy on LibriSpeech, trains three times faster than LSTM, halves model size, and dramatically speeds up real‑time decoding.

DFSMNDeep Learningacoustic modeling

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How DFSMN Sets a New Record in Speech Recognition Accuracy and Speed