Hindi Call Center Conversation Dataset – Real customer-agent dialogues for AI and speech model ...

This dataset includes authentic Hindi-language call center conversations between customers and support agents. It provides real, unscripted spoken interactions sourced from contact centers across sectors such as finance, telecom, logistics, retail, and services — enabling AI teams to build tools that understand how Hindi-speaking customers interact in live support scenarios. All recordings are: - Original, not synthetically generated - Captured from real customer-agent interactions across 160+ industries - Available in WAV, FlAC and aligned with transcriptions Each record includes: - Raw audio file of the customer service call (typically 3–15 minutes) - Accompanying human transcription and summary - Call duration, timestamp, and caller location (city, state, country) - Sentiment label: positive, neutral, or negative - Company reference (optional) Use this dataset to: Use this dataset to: - Train speech-to-text systems on real Hindi support dialogue - Build conversational AI and voicebots for Hindi-speaking users - Analyze tone, frustration, and resolution flow in call center operations - Benchmark and QA agent performance using real call scenarios - Support accent-aware model adaptation for Indian regional speech patterns The conversations reflect real challenges, emotional dynamics, and spoken patterns common to Indian call centers — making it an essential foundation for AI products serving Hindi-speaking markets.

搜集汇总

背景与挑战

背景概述

该数据集包含来自金融、电信等多个行业的真实印地语客服对话音频，配有转录、元数据及情感标签。它可用于训练语音转文本系统、构建对话AI以及分析客服场景中的情感和互动模式，是服务印地语市场的AI产品的重要基础。