SETU用智能代理系统帮销售人员跨语言适配客户沟通，报告可解释且可审计。
SETU: An Agentic Ecosystem for Multilingual, Persona-Aware Communication Coaching
- 分模块代理协同分析音视频文本，按模态生成针对性反馈
- 在销售场景中实现目标受众适配，报告支持形式化训练
- 适合企业培训、招聘与销售团队使用，强调可解释性与可控性
企业培训团队亟需可扩展且可解释的工具，以提升多语言环境下的员工沟通能力。现有系统常孤立评估文本、音频或视频，或生成难以审计的黑箱输出，不适用于教练场景。本文提出SETU，一个面向招聘与销售场景的智能代理生态系统，旨在帮助招聘人员、一线销售及培训团队准备针对特定受众的对话。该系统聚焦两个应用场景：(i) 带人物角色背景的候选人资格与兴趣通话；(ii) 针对目标受众调整的销售推介。受限于评估资源，本文仅报告场景(ii)的结果。SETU将分析分解为视频、语音、文本相关性、评分、通知和报告等专业化代理，通过可信度感知的编排机制协同工作。系统生成带有模态归属的教练报告，用于形成性训练，最终判断仍由人工评审保留。名称SETU（印地语等印度语言中意为‘桥梁’）体现了跨越区域语言与受众期待鸿沟的目标。
原文摘要 · Abstract (English)
Corporate training teams need scalable and explainable tools to improve workforce communication in multilingual settings. Existing systems often score text, audio, or video in isolation, or produce black-box outputs that are difficult to audit for coaching use. This paper presents SETU, an agentic ecosystem for corporate communication coaching aimed at recruiters, frontline sales professionals and training units who prepare for audience specific conversations. SETU is designed for two scoped scenarios: (i) recruiter-candidate eligibility-and-interest calls with persona context and (ii) sales pitches with target-audience adaptation; owing to limited evaluation resources, this paper reports results on scenario (ii) only. The ecosystem decomposes analysis into specialized video, audio-speech, text-relevance, scoring, notification and reporting agents coordinated through trust-aware orchestration. It generates modality-attributed coaching reports for formative training, with human reviewers retaining final judgment. The name SETU (bridge in several Indic languages) reflects the goal of bridging communication gaps across regional languages and audience expectations.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。