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.
This article presents a comprehensive study on slot (entity) recognition and error correction for voice robots, describing the labeling scheme, data annotation, IDCNN+CRF and BiLSTM+CRF models, a pinyin‑based similarity algorithm, and reporting significant accuracy improvements in real‑world deployments.
The article reviews the design and implementation of 58.com’s intelligent voice robot backend, detailing its four‑layer architecture, SIP/SDP/RTP protocols, multi‑round voice interaction flow, algorithm service modularization, SIP scheduling optimizations, and Java thread‑pool system tuning for high‑concurrency scenarios.
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.
This article explains how Alibaba leveraged AI‑powered voice robots to handle massive outbound call volumes during COVID‑19, detailing the technology stack, real‑world application scenarios across finance and retail, and the future potential of intelligent voice assistants in customer service.
This article presents a complete solution for 58.com’s human‑machine voice dialogue robot, detailing its background, overall architecture, intelligent outbound process, core functions such as call service, anti‑spam, status recognition, multi‑turn dialogue management, intent classification, slot extraction, whole‑round intent detection, and various practical application scenarios.
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.
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.
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.
