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This article describes the overall architecture of 58.com’s multi‑turn voice robot, explains rule‑based, intent‑based and text‑matching dialogue jump strategies, introduces an end‑to‑end classification approach using TextCNN, and reports its online performance improvements and future research directions.
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During the COVID‑19 pandemic, Alipay deployed AI‑enabled intelligent voice robots to handle massive call volumes, detailing the underlying technologies such as imitation learning, reinforcement learning, few‑shot intent recognition, and user simulation, while outlining current applications across finance, retail, security, and future prospects for automated customer service.
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This article details the architecture and algorithms behind a voice robot's natural language understanding module, covering single‑sentence intent classification with TextCNN, acoustic quality detection using VGGish‑BiLSTM, semantic similarity matching via DSSM and TextCNN‑Transformer, and slot‑filling with IDCNN‑CRF, along with performance results and future directions.
This article presents a comprehensive overview of an intelligent voice robot's dialogue management system, detailing its architecture, natural language understanding components, dialogue manager design, strategy handling, and workflow processes to achieve fluent multi‑turn interactions in telephone scenarios.
The article describes the design and implementation of a voice robot platform, covering its background, layered architecture, dialogue flow, intent recognition techniques, micro‑service backend, and future improvements, highlighting how AI models and telephony integration enable automated multi‑turn voice interactions for sales and service scenarios.
This article details the architecture and implementation of the voice call module of an intelligent voice robot, covering SIP signaling establishment, RTP session handling, audio encoding/decoding, sampling, and packetization to enable automated outbound calls and multi‑round voice interactions.