What Is Synthetic training data?
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…
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.
Industrialize training data production for any voice-controlled device, chatbot or IVR using artificial training data.
- Recognize a user´s intent in any chatbot platform: Dialogflow, MS-LUIS, RASA…
- Enjoy 90% accuracy, guaranteed by SLA
Machine Learning is one of the most common use cases for Synthetic Data today, mainly in images or videos.
3 main problems of AI data:
- scarcity of data, tens of thousands of utterances per intent
- no privacy / GDPR issues, no anonymization needed
- scalable process, for different bots and different languages
Bitext Synthetic Training Data can resolve all of those 3 problems listed above and We offer text training data in any language you need. Quickly scale or increase the amount of data in a fast and flexible way.
Take a Look to our GitHub Repository and access to our Dataset to try it by yourself.
Multilingual Training datasets for intent detection
We help you understand your customers either
- if you do not have any existing training data and are getting started with your chatbot
- if you need to increase the accuracy of your existing bot
- if you need to expand your bot to other languages and want to keep the same accuracy across languages
What If I already have an existing training data?
Bitext has solutions for your current bot and for your new bot.
- If you want to increase the accuracy or expand the scope of your current assistant/chatbot with more intents and utterances, we automate the process and generate the training data you need in any language.
- Our Quality Assurance and Improvement service allows to retrain the model regularly, to increase accuracy up to 90%, guaranteed by SLA.
- We offer different options according to your needs. From our pre-built vertical templates (bootstrapping) covering the most common intents for each vertical, to custom datasets for customer specific requests.
Next step, after training , is to evaluate data. We explain better this proccess with Unstructured Synthetic Text topic. Take a look!