India’s digital ecosystem is growing at a rapid pace. Artificial Intelligence is quickly becoming integrated into our day-to-day lives: while searching for information online, making purchases, and engaging in transactions. However, developing AI models that can succeed in such a competitive environment is a challenging endeavor. India’s linguistic diversity makes it a unique region, and AI models need accurate, representative language data to perform their tasks correctly. Indic Language Data Services can facilitate the incorporation of Indian languages and dialects into your AI/ML technologies.
What are Indic language data services?
Indic language data services are solutions that address the collection, creation, curation, annotation, evaluation, and validation of language data for Indian languages and dialects. The collected data can fuel various AI and ML applications, including text, speech, conversational AI, search, recommendation systems, and generative AI.
Indian languages can be highly contextual, use different scripts, writing systems, and have varying degrees of formality and colloquialisms. Language data, annotated with relevant linguistic phenomena, can assist in training AI models to recognize and account for these variations during their operation and, therefore, produce better results.
Why is indic language data important for AI?
Modern AI models require vast amounts of data to function correctly. If the training data lacks representations of India’s linguistic diversity, the model will have a poor understanding of the language and, therefore, perform poorly.
Indic language data sets can be utilized for training and evaluating large language models, language understanding and processing systems, and various other AI applications, including search and question-answering systems, recommendation engines, conversational AI, chatbots, and more.
Indic language data sets can enable organizations to build effective AI models that will be able to adapt to the complexities of the linguistic landscape in India.
Indic language data services catalog
The wide scope of services covered by Indic language data services can be overwhelming. We’ve separated the most common services into distinct categories to help you determine which of them might be of interest to your organization.
Text data collection
Collect and curate text corpora in various Indian languages to support the needs of your ML models and AI applications.
Annotation
Augment the collected text data with information relevant to training and testing your ML/AI models.
Speech and audio data collection
Speech recognition and conversational AI require vast amounts of audio data. We can collect and curate data sets with speech samples from different speakers, regional accents, and levels of formality.
Transcription and validation
Validate the quality and consistency of collected data sets and correct possible transcription errors.
Dialect and regional data
Indian languages have many regional and local variations. We can collect and curate speech and text data sets with local flavor, slang, and other unique elements.
AI data evaluation
Linguistic data sets and AI-generated text can be evaluated for quality, consistency, and linguistic appropriateness.
Multilingual and generative AI
The popularity of generative AI methods and applications keeps growing, and multilingual language models are at the forefront of this development.
Indic language data Services are vital for any organization that wants to develop large-scale AI applications, including chatbots, search systems, recommendation engines, AI voice assistants, and more.
When designing and training AI applications for consumers and businesses in India, it is essential to utilize data sets that reflect India’s linguistic diversity during the training and testing phases.
The value of data quality
Quantity of data is not the only determining factor; rather, its quality, structure, complexity, and consistency play an equally important role. The data curation workflow, annotation guidelines, inter-annotator agreement, and validation and review stages are essential for linguistic data sets. The expertise of linguistic professionals and domain experts is also crucial for any language-related data annotation task. Additionally, data structure and required transformations need to be thoroughly discussed and formalized.
Quality control, data preparation, and augmentation techniques, when applied correctly and in a linguistically informed way, can lead to higher data quality and, ultimately, a better-performing model.
Summary
As the use of AI becomes ubiquitous, India’s regional languages and linguistic diversity will need to be considered during the development and training phases of AI applications. Utilizing, Indic Language Data Services can help you prepare, train, test, and evaluate your AI models and applications. Through quality data annotation and validation, as well as careful consideration of language specifics, we can help you design AI applications and tools that will be well-suited for the rapidly evolving Indian market.
