This article details HuoLaLa's development of an in‑house Automatic Speech Recognition system, covering its architecture, VAD optimization, language‑model and hot‑word enhancements, punctuation restoration, task and resource scheduling, and the resulting improvements in accuracy and cost efficiency.
This article presents the design, training, deployment, and evaluation of a self‑developed Voice Activity Detection system used in both real‑time streaming dialogues and offline audio analysis at 58.com, detailing algorithm choices, smoothing strategies, engineering challenges, and future research directions.
This article details how a three‑person team at 58.com built a self‑developed speech recognition engine in less than a year, covering background, team formation, data annotation, model selection, engineering architecture, performance optimizations, deployment results, and future directions.
This article details the evolution of the voice endpoint detection (VAD) module in 58.com’s voice robot, comparing a dual‑threshold method, Google’s WebRTC VAD, and the deep‑learning based VADNet, and presents experimental results on accuracy, recall, F1 score and online latency.
