Hindi Call Center Speech Dataset for Healthcare

This Hindi Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of Hindi speech recognition, spoken language understanding, and conversational AI systems. With 30 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

The dataset features 30 Hours of dual-channel call center conversations between native Hindi speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

This dataset can be used across a range of healthcare and voice AI use cases:

We continuously enrich this dataset and offer fully customizable collection services:

This Healthcare call center speech dataset is created by FutureBeeAI and is available under a commercial license for enterprise and research deployment.