Boosting Online Speech Recognition with Improved Latency‑Controlled BLSTM Models

This article explains how improved latency‑controlled BLSTM acoustic models can boost online speech‑recognition accuracy while cutting decoding computation, detailing two model refinements that achieve 40‑60% speed gains with minimal loss in recognition performance.

Computational EfficiencyDeep LearningLC-BLSTM

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Boosting Online Speech Recognition with Improved Latency‑Controlled BLSTM Models

Alibaba Cloud Developer

Mar 17, 2017 · Artificial Intelligence

How Improved Latency‑Controlled BLSTM Models Boost Online Speech Recognition Efficiency

This article explains how latency‑controlled BLSTM acoustic models were refined to accelerate online speech recognition while preserving accuracy, detailing the training strategy, computational trade‑offs, and two model enhancements that achieve up to 60% faster decoding with modest resource savings.

Deep LearningLC-BLSTMacoustic modeling

0 likes · 6 min read

How Improved Latency‑Controlled BLSTM Models Boost Online Speech Recognition Efficiency