Introduction

The Hindi General Domain Chat Dataset is a high-quality, text-based dataset designed to train and evaluate conversational AI, NLP models, and smart assistants in real-world Hindi usage. Collected through FutureBeeAI’s trusted crowd community, this dataset reflects natural, native-level Hindi conversations covering a broad spectrum of everyday topics.

Conversational Text Data

This dataset includes over 15000 chat transcripts, each featuring free-flowing dialogue between two native Hindi speakers. The conversations are spontaneous, context-rich, and mimic informal, real-life texting behavior.

Diversity and Domain Coverage

Conversations span a wide variety of general-domain topics to ensure comprehensive model exposure:

This diversity ensures the dataset is useful across multiple NLP and language understanding applications.

Linguistic Authenticity

Chats reflect informal, native-level Hindi usage with:

Metadata

Every chat instance is accompanied by structured metadata, which includes:

This metadata supports model filtering, demographic-specific evaluation, and more controlled fine-tuning workflows.

Data Quality Assurance

All chat records pass through a rigorous QA process to maintain consistency and accuracy:

This ensures a clean, reliable dataset ready for high-performance AI model training.

Applications

This dataset is ideal for training and evaluating a wide range of text-based AI systems:

Home Hindi Datasetहिंदी डेटासेटHigh-Quality Hindi Call-Center, General Conversation, and Podcast Dataset for AI & ASR Models Contact Us OverviewTitle (Language)Hindi Language DatasetDataset TypesCall Center, General Conversation, Media (Podcast), Scripted MonologueCountryIndiaDescriptionUnscripted…

Introduction

The Hindi Healthcare Chat Dataset is a rich collection of over 12,000 text-based conversations between customers and call center agents, focused on real-world healthcare interactions. Designed to reflect authentic language use and domain-specific dialogue patterns, this dataset supports the development of conversational AI, chatbots, and NLP models tailored for healthcare applications in Hindi-speaking regions.

Participant & Chat Overview

Topic Diversity

The dataset captures a wide spectrum of healthcare-related chat scenarios, ensuring comprehensive coverage for training robust AI systems:

This variety helps simulate realistic healthcare support workflows and patient-agent dynamics.

Language Diversity & Realism

This dataset reflects the natural flow of Hindi healthcare communication and includes:

These elements ensure the dataset is contextually relevant and linguistically rich for real-world use cases.

Conversational Flow & Structure

Conversations range from simple inquiries to complex advisory sessions, including:

Each conversation typically includes these structural components:

This structured flow mirrors actual healthcare support conversations and is ideal for training advanced dialogue systems.

Data Format & Structure

Available in JSON, CSV, and TXT formats, each conversation includes:

Applications

Explore high-quality Hindi general conversation speech datasets for AI, NLP, and speech recognition research. Download and enhance your projects today!

This dataset contains 34 hours of Hindi children’s speech.The recordings cover self-media, conversations, live talk, lectures, variety show and other generic domains, mirrors real-world interactions. Each utterance is transcribed with text content, speaker's ID, gender, age, accent and other attributes. Our dataset was collected from extensive and diversify speakers(12 years old and younger children), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Introduction

Welcome to the Hindi General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Hindi speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Hindi communication.

Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Hindi speech models that understand and respond to authentic Indian accents and dialects.

Speech Data

The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Hindi. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

Topic Diversity

The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

Transcription

Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

Metadata

The dataset comes with granular metadata for both speakers and recordings:

Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

Usage and Applications

This dataset is a versatile resource for multiple Hindi speech and language AI applications:

This dataset contains 760 hours of spontaneous Hindi dialogue speech, collected from dialogues based on given topics, covering 20+ domains. Transcribed with text content, speaker's ID, gender, age and other attributes. Our dataset was collected from extensive and diversify speakers(1,004 native speakers), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Hindi Telephone Dialogues Dataset - 760 Hours

Dataset comprises 760 hours of high-quality audio recordings from 1,000+ native Hindi speakers, featuring telephone dialogues across diverse topics and domains. With a 95% sentence accuracy rate, this essential dataset is ideal for training and evaluating Hindi speech recognition systems. - Get the data

  Dataset characteristics:

Characteristic Data

Description Audio of telephone dialogues in Hindi for training… See the full description on the dataset page: https://huggingface.co/datasets/ud-nlp/hindi-speech-recognition-dataset.

The audio dataset includes General Conversation, featuring Hindi speakers from India with detailed metadata.

Boost AI capabilities with our real-world call center audio data. Consented recordings in Hindi, covering industries like e-commerce, banking, insurance and medicine.

This dataset contains 797 hours of spontaneous Hindi dialogue speech, collected from dialogues based on given topics, covering 20+ domains. Transcribed with text content, speaker's ID, gender, age and other attributes. Our dataset was collected from extensive and diversify speakers(1,022 native speakers), geographicly speaking, enhancing model performance in real and complex tasks. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Introduction

The Hindi Delivery & Logistics Chat Dataset is a comprehensive collection of over 12,000 text-based conversations between customers and call center agents. Focused on real-world delivery and logistics interactions, this dataset captures the language, tone, and service patterns essential for developing robust Hindi-language conversational AI, chatbots, and NLP systems across the delivery ecosystem.

Participant & Chat Overview

Topic Diversity

The dataset spans a wide range of delivery and logistics scenarios, ensuring strong coverage across customer service and operational workflows.

This topical spread ensures wide applicability in both customer support automation and logistics optimization use cases.

Language Diversity & Realism

The conversations reflect the authentic language and interaction style of Hindi-speaking customers and delivery agents, incorporating:

This linguistic realism enables the development of context-aware and naturally responsive AI systems.

Conversational Structure & Flow

The dataset captures a diverse range of interaction types and delivery workflows:

Introduction

The Hindi Real Estate Chat Dataset is a high-quality collection of over 12,000 text-based conversations between customers and call center agents. These conversations reflect real-world scenarios within the Real Estate sector, offering rich linguistic data for training conversational AI, chatbots, and NLP systems focused on property-related interactions in Hindi-speaking regions.

Participant & Chat Overview

Topic Diversity

The dataset spans a broad range of Real Estate service conversations, covering various customer intents and agent support tasks:

This topic variety enables realistic model training for both lead generation and post-sale engagement scenarios.

Language Nuance & Authenticity

Conversations are reflective of natural Hindi used in the Real Estate domain, incorporating:

This level of linguistic realism supports model generalization across dialects and user demographics.

Conversational Structure & Flow

Conversations include a mix of short inquiries and detailed advisory sessions, capturing full customer journeys:

A curated dataset of colloquial English phrases and their corresponding Hindi translations. This dataset focuses on informal language, including slang, idioms, and everyday expressions, making it ideal for training models that handle casual conversations. Dataset Details: Size:e.g., 500+ phrase pairs] Source: Collected from publicly available conversational datasets, social media, and crowdsourced contributions. Language Pair: English → Hindi Annotations: Each phrase pair is manually verified… See the full description on the dataset page: https://huggingface.co/datasets/bajpaideeksha/english-hindi-colloquial-dataset.

Download the comprehensive Call Center Conversations Speech Dataset in Hindi, focused on the BFSI sector. Ideal for AI training, speech recognition, and customer service analytics.

Indic Instruct Data v0.1

A collection of different instruction datasets spanning English and Hindi languages. The collection consists of:

Anudesh wikiHow Flan v2 (67k sample subset) Dolly Anthropic-HHH (5k sample subset) OpenAssistant v1 LymSys-Chat (50k sample subset)

We translate the English subset of specific datasets using IndicTrans2 (Gala et al., 2023). The chrF++ scores of the back-translated example and the corresponding example is provided for quality assessment of the… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1.

Hindi Colloquial Dataset

This dataset contains pairs of English Text and Hindi Colloquial Text, designed for training machine learning models for translation . The dataset was created as part of a hackathon organized by Swati.

  Dataset Details

Size: 90 pairs of English and colloquial Hindi sentences Languages: English, Hindi Task: Translation, Text Generation Content: Contains colloquial translations for everyday conversational texts in Hindi.

  Example… See the full description on the dataset page: https://huggingface.co/datasets/SirirshaD/hindi-colloquial-dataset.

Introduction

The Hindi Retail & E-Commerce Chat Dataset is a large-scale, high-quality collection of over 12,000 chat conversations between customers and call center agents, focused exclusively on Retail and E-Commerce domains. Designed to reflect real-world service interactions, this dataset supports the development of robust conversational AI and NLP models tailored for Hindi-speaking audiences.

Participant & Chat Overview

Topic Diversity

This dataset spans a wide range of Retail and E-Commerce conversation types:

This diversity enables training of models that handle varied intents, scenarios, and outcomes within customer service workflows.

Language Nuance & Realism

The dataset is rich in linguistic diversity and mirrors real conversational tone and structure used in Hindi-speaking regions:

This linguistic authenticity ensures the development of culturally fluent AI models for Hindi Retail & E-Commerce use cases.

Conversational Structure & Flow

The conversations reflect natural dialogue dynamics and are organized into various types of interaction styles:

Each conversation includes common dialogue stages such as:

Akèy Ansanm Done Hindiहिंदी डेटासेट Ansanm Done Sant Apèl, Konvèsasyon Jeneral, ak Podcast Hindi Kalite Siperyè pou Modèl IA ak ASR Kontakte nou Apèsi sou sijè aTit (Lang)Ansanm Done Lang HindiTip Ansanm DoneSant Apèl, Konvèsasyon Jeneral, Medya (Podcast), Monològ ak SenaryoPeyiEndDeskripsyonSan Senaryo…