Indian English General Conversation Speech Dataset

This dataset captures real-world, unscripted conversations between native Indian English speakers. It includes detailed metadata and high-quality manual transcriptions, making it ideal for building accurate, human-like speech recognition and conversational AI systems.

About this Off-the-shelf Speech Dataset

Introduction

Welcome to the Indian English General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of English 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 Indian English 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 English 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 Indian English. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

•Participant Diversity:

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Speakers: 60 verified native Indian English speakers from FutureBeeAI’s contributor community.

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Regions: Representing various provinces of India to ensure dialectal diversity and demographic balance.

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Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.

•Recording Details:

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Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.

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Duration: Each conversation ranges from 15 to 60 minutes.

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Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.

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Environment: Quiet, echo-free settings with no background noise.

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.

•Sample Topics Include:

•Family & Relationships

•Food & Recipes

•Education & Career

•Healthcare Discussions

•Social Issues

•Technology & Gadgets

•Travel & Local Culture

•Shopping & Marketplace Experiences, and many more.

Transcription

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

•Transcription Highlights:

•Speaker-segmented dialogues

•Time-coded utterances

•Non-speech elements (pauses, laughter, etc.)

•High transcription accuracy, achieved through double QA pass, average WER < 5%

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:

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Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.

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Recording Metadata: Topic, duration, audio format, device type, and sample rate.

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 English speech and language AI applications:

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ASR Development: Train accurate speech-to-text systems for Indian English.

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Voice Assistants: Build smart assistants capable of understanding natural Indian conversations.

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Conversational AI: Develop chatbots and voicebots for multilingual or dialectal English audiences.

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Speech Analytics: Extract patterns, detect topics, and evaluate speaker behavior.

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Generative Voice AI: Enable real-life dialogue synthesis or summarization with native-sounding output.

Secure and Ethical Collection

•All data was collected using “Yugo,” FutureBeeAI’s proprietary collection and transcription platform.

•Data remained within a secure environment throughout the process.

•Collected in compliance with strict privacy, consent, and ethical guidelines.

•No personally identifiable information is included in any recording or transcript.

•Free of copyrighted content. Safe for commercial and research use.

Customization and Updates

We continuously enrich this dataset with new, naturally captured conversations. Additionally, we support project-specific data customization:

•Available Customization:

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Acoustic Conditions: In-car, restaurant, outdoor, or noisy environments on request.

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Sampling Rate: Custom WAV files at 8kHz to 48kHz.

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Transcription Guidelines: Tailored formatting, annotation levels, or QA standards.

License

This Indian English General Conversation Dataset is created by FutureBeeAI and is available for commercial licensing.

Use Cases

Use of speech data for Automatic Speech Recognition

ASR

Conversational AI

Chatbot

Language Modelling

TTS

Speech Analytics

Dataset Sample(s)

Dataset Details

Language

English

Language code

en-In

Country

India

Accents

Chandigarh, Chhattisgarh ...moreDelhi, Gujarat, Jammu and Kashmir, Kerala, Madhya Pradesh, Maharashtra, Odisha, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, Uttarakhand, West Bengal

Gender Distribution

M:55, F:45

Age Group

18-70 Years