Improving annotation with multilingual data labelling and AI/ML
We live and work in an incredibly interconnected world. People speak different languages, work in various geographies and multilingual environments, and access text, audio, images, and video content in multiple languages. It would be imprudent to ignore the influence of a multi-lingual world from data management, labelling, and content annotation perspectives.
The influence of multiple languages is not restricted to the inner workings of a business either. In terms of gaining a competitive edge and delivering a better customer experience, modern businesses are striving to enhance their annotation processes with multilingual data labelling.
Businesses that serve both customers and employees across geographies with multilingual support can gain a wide range of benefits. Global businesses are steadily integrating self-learning artificial intelligence (AI) and machine learning (ML) models into their processes in order to:
- Enhance operational efficiency
- Maximise human capability
- Improve the customer experience
However, for any AI/ML model to really succeed, you need to train these models using a vast volume of structured data via a smart annotation and labelling process. Here’s how forward-looking enterprises can improve data annotation and labelling by training AI and ML models in multiple languages.*
Key considerations for businesses
Google Translate is a useful tool for individual users looking for text and voice translation solutions at their fingertips. However, there is absolutely no way a business can rely on this service for internal communications, customer service, or growth.Language data annotation calls for extreme precaution and a high level of expertise because any kind of data (in the source language) has some meaning and context attached to it. The misinterpretation of the context or meaning could have an undesirable effect on the ML output.
How to improve annotation with multilingual data labelling and AI/ML?
Several industry leaders across various sectors, including Google, Microsoft, and Facebook, have evolved their AI models to include and offer content in multiple languages. When data is available in various forms, annotation and labelling basically make it easy for the ML platform to read and understand. For more clarity, additional metadata or notes may be added to the data tags. When this data annotation is applied to an entire piece of content (a text, an audio, or a video), AI-based models can decipher and comprehend it.
Now, human-annotated datasets form the basis for AI algorithms. So, when we talk about multilingual data labelling and AI/ML, it is the annotation that determines its accuracy, reliability, and overall success. It is essential that experts are roped in for any kind of translation and localisation (inward and outward). Language data annotation or multilingual data labelling, in this case, becomes a critical step because it lays down the foundation for your AI and ML models to apply it across larger datasets.
How can Infosys BPM help?
The biggest challenge is finding professional annotators who can take raw datasets and deliver trainable datasets based on predefined parameters, ensuring the required output quality. While automated data labelling delivers unparalleled speed, manual intervention is necessary for quality control. And, that is where Infosys BPM can help you accelerate AI/ML projects through its hybrid model.
With a ready-to-deploy pool of expert annotators who work as an extension of your AI team, we work on a flexible and scalable managed services operating model. Our annotation service span areas like text, image, audio, video, and sensor data tagging and segmentation. Our tie-ups with industry-leading training data platforms allow us to combine human capability with state-of-the-art intelligent automation to increase speed to market.
Learn more about how Infosys BPM can help you improve your annotation efforts with multilingual data labelling and AI/ML.
*For organisations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed organisational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive yet modular suite of services is doing exactly that. Equipping organisations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organisations that are innovating collaboratively for the future.