Synthetic image and video have proven to be a big success for cost-cutting. Synthetic text is following suit: tabular data (that is the data organized in a table with rows and columns) is becoming mainstream already, and the next step is synthetic unstructured text, which is the data that doesn`t have a predefined format.
Synthetic unstructured text supports more complex cases, where actual text in the form of full sentences or documents is required.
Synthetic Training data is the data that is used to train an NLU engine. An NLU engine allows chatbots to understand the intent of user queries. The training data is enriched by data labeling or data annotation, with information about entities, slots…
When shopping online, customers frequently have the need to modify their order: exchanging an item in the basket, deleting something already added…
Training data is the data that is used to train an NLU engine. An NLU engine allows chatbots to understand the intent of user queries.
The training data is enriched by data labeling or data annotation, with information about entities, slots…
This training process provides the bot with the ability to hold a meaningful conversation with real people.
After the training process, the bot is evaluated to measure the accuracy of the NLU engine. Evaluation identifies errors in the bot behavior and these errors are then fixed by improving training data. This cycle is repeated
When working on AI projects, owning data to nurture your solution is key for good performance.
