Language Datasets
Licensed, consent-sourced speech, TTS & ASR data in 18+ Indian languages in diverse accents and styles
Indian language datasets are licensed collections of speech, audio, and text data across Indian languages such as Hindi, Bengali, Tamil, Telugu, and Marathi, used to train ASR, text-to-speech, and NLP models. Shaip delivers consent-sourced Indian language datasets — off-the-shelf or custom-collected — in 18+ languages with native-speaker validation. Whether you’re working on speech recognition, text-to-speech, or natural language processing, our expertly validated Indic audio data—including conversational dialogues, scripted recordings, and IVR samples—provides the reliable foundation you need for success.
Speech Data
Call-Center, General Conversation, Podcast
Assamese Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Bengali Dataset View More
Speech Data
General Conversation, TTS
Dogri Dataset View More
Speech Data
General Conversation, TTS
Gojri Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Gujarati Dataset View More
Speech Data
General Conversation, Podcast, TTS
Hindi Dataset View More
Speech Data
Call-Center,
Podcast
Hinglish Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Kannada Dataset View More
Speech Data
General Conversation, TTS
Kashmiri Dataset View More
Speech Data
General Conversation, Podcast
Malay Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Malayalam Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Marathi Dataset View More
Speech Data
General Conversation, TTS
Nagamese Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Oriya Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Punjabi Dataset View More
Speech Data
Call-Center, General Conversation, Podcast
Tamil Dataset View More
Speech Data
General Conversation, Podcast
Telugu Dataset View More
Speech Data
Wake Word / Keyphrase
Wake Word Indian English Dataset View More
Speech Data
Wake Word / Keyphrase
Wake Word Indian English Dataset View More
End-to-end service: Complete service with expert domain knowledge and fast delivery.
Flexible: Choose custom, semi-custom, or off-the-shelf voice datasets with flexible ownership.
Domain Expert: Hire a Specialized Domain Expert for Fast, Quality AI Datasets.
Quality: Get quality checks from industry experts.
Licensing: Get a license tailored to your needs.
Ethical Data: We ensure contributors are informed and consent to data use.
Train virtual agents to understand and speak Indian languages naturally.
Build high-accuracy TTS engines for Hindi, Bengali, Tamil, and more.
Improve transcription and voice command accuracy for regional languages.
Enable seamless translation between Indian languages and English.
Extract medical data from Indian language records and doctor-patient conversations.
Support multilingual search, product recommendations, and voice-based ordering.
Shaip collects scripted, spontaneous, and conversational Indian-language speech across call-center, podcast, IVR, and general-conversation domains. Native collectors capture authentic accents and dialects, then linguists transcribe and validate every recording for ASR and voice-AI training.
Shaip builds studio-grade and natural TTS corpora for Indian languages, pairing clean phonetically-balanced scripts with professional voice talent. Each TTS dataset supports expressive, multi-speaker synthesis for Hindi, Bengali, Tamil, Telugu, and additional Indic languages.
Shaip delivers transcription-aligned audio for automatic speech recognition, including code-switched Hindi-English (Hinglish) and Indian-English dialects. Standardized transcription guidelines cover spelling, disfluencies, and non-speech events to maximize recognition accuracy across regional variants.
Shaip provides annotated Indian-language text for translation, sentiment, intent, and entity tasks. Datasets capture script, romanized, and code-mixed text so NLP and LLM teams can train models that handle India's real-world multilingual input.
Choose pre-labeled off-the-shelf Indian datasets for fast deployment, or commission custom collection by language, dialect, demographic, and domain. Flexible licensing and ownership terms let teams scale from a pilot to a full production corpus without renegotiating consent.
Shaip captures multi-turn dialogue, utterance variations, and wake-word data for Indian-language virtual assistants and IVR systems. Utterance sets reflect how real users phrase the same intent, improving recognition for chatbots and voice agents in Hindi and regional languages.
At Shaip, we provide diverse speech datasets for NLP that mimic real conversations to enhance your AI. Our expertise in Multilingual Conversational AI helps you create precise speech models. We offer multilingual audio collection, transcription, and annotation services, customized to your needs for intent, utterances, and demographics.
Scripted Speech Collection
Spontaneous Speech collection
Utterance Collection/ Wake-up Words
Automated Speech Recognition (ASR)
Transcreation
Text-to-speech (TTS)
Shaip provided digital assistant training in 40+ languages for a major cloud-based voice service provider used with voice assistants. They required a natural voice experience so users in different countries around the world would have intuitive, natural interactions with this technology.
Problem: Acquire 20,000+ hours of unbiased data across 40 languages
Solution: 3,000+ linguists delivered quality audio/ transcripts within 30 weeks
Result: Highly trained Digital assistant models that is able to understand multiple languages
Not all customers use the same words while interacting with voice assistants. Voice applications must be trained on spontaneous speech data. E.g., “Where is the closest hospital located?” “Find a hospital near me” or all indicate the same search intent but are phrased differently.
Problem: Acquire 22,250+ hours of unbiased data across 13 languages
Solution: 7M+ Audio Utterances collected, transcribed, and delivered within 28 weeks
Result: Highly trained speech recognition model that is able to understand multiple languages
Specify languages, dialects, formats, demographics, and volume for your Indian-language dataset.
Native speakers contribute consent-sourced speech, audio, or text under standardized protocols.
Linguists transcribe, label, and tag data to your guidelines for ASR, TTS, or NLP.
6-Sigma QA validates every file, then Shaip delivers licensed data in your required format.
Shaip operates a vetted network of 500k+ collaborators for collection, labeling, and QA across Indian languages, backed by a credentialed project-management team. This scale lets Shaip staff native speakers for any Indian language or dialect on demand.
Shaip runs a 6-Sigma stage-gate process with dedicated black belts owning quality compliance. A continuous feedback loop drives consistent accuracy across every Indian-language speech, TTS, and transcription deliverable.
Every Indian language dataset is consent-sourced and GDPR-aligned, with informed contributor agreements and flexible licensing. Teams receive clear ownership terms — unlike open corpora that carry research-only or attribution restrictions.
Empowering teams to build world-leading AI products.
Contact us now to learn how we can collect a custom data set for your unique AI solution.
Indian language datasets are collections of text, audio, and speech data in various Indian languages like Hindi, Tamil, Bengali, and Assamese, used to train AI/ML models for multilingual applications.
These datasets help AI/ML systems understand and process diverse regional languages, enabling accurate natural language processing, intent recognition, and conversational AI for multilingual users.
They provide high-quality, annotated data in multiple languages, allowing AI models to learn speech patterns, accents, and linguistic nuances, which improves the performance of voice assistants, chatbots, and other conversational AI systems.
Shaip offers 18+ Indian languages, including Hindi, Bengali, Tamil, Telugu, Gujarati, Marathi, Kannada, Malayalam, Punjabi, Assamese, Oriya, Hinglish, and Indian English, plus low-resource languages such as Dogri and Kashmiri. Each language is available as off-the-shelf speech data or custom collection covering regional dialects and accents.
Indian language datasets are used to train voice assistants, enhance text-to-speech systems, improve automated speech recognition, and support multilingual applications in industries like healthcare, e-commerce, and customer service.
Scripted speech data is pre-written and read aloud, ensuring consistency, while spontaneous speech captures natural conversations, providing more realistic data for training AI systems.
Yes, datasets can be tailored to meet specific requirements like language, accents, demographics, or use cases, ensuring they align with unique project needs.
All datasets are collected with informed consent and adhere to global privacy regulations like GDPR, ensuring ethical and secure data handling.
Timelines depend on project size and complexity but are structured to ensure fast and efficient delivery.
Quality is maintained through expert annotators, rigorous validation processes, and industry-standard quality assurance measures.
Costs vary based on language, dataset size, customization, and project requirements. Contact for a personalized quote.
High-quality, annotated datasets provide the linguistic diversity and real-world examples needed to train, validate, and fine-tune NLP models. This leads to more accurate and natural interactions with Indian language users.
Open corpora such as IndicVoices and IndicCorp are valuable for research but typically carry research-only or attribution licences and fixed scope. Shaip provides commercially-licensed, consent-sourced Indian language datasets with custom collection by dialect, demographic, and domain, full ownership options, and 6-Sigma QA — so teams can deploy in production without licensing risk.
Yes. Shaip delivers TTS corpora with phonetically-balanced scripts and professional voice talent, and ASR datasets with transcription-aligned audio across Indian languages, including code-switched Hinglish. Both formats follow standardized guidelines for transcription, pronunciation, and audio quality to support production speech models.
