Multilingual Synthetic Training Data
Industrialize training data production for any voice-controlled device, chatbot or IVR using artificial training data.
- Recognize a user´s intent in any platform
- Improve up to 90% accuracy
Working with 3 of the Top 5 largest companies in NASDAQ
Multilingual Training datasets for intent detection
We help you understand your customers either if you do not have any existing training data or need to increase your accuracy or expand to other languages with consistency.
Our Solution, for your current bot and for your new bot
Machine Learning is one of the most common use cases for Synthetic Data today mainly in images or videos. We offer text training data in any language you need. Quickly scale or increase the amount of data in a fast and flexible way.
If you have existing training data
- If you want to increase the accuracy or expand the scope with more intents or utterances, we can 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.
Generation of multilingual training data
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.
- We can add advanced module datasets covering regional variants, politeness, expanded abbreviations, offensive or small talk…
Each Instant Chatbot contains the 20 to 40 most frequent intents for the corresponding vertical, designed to give you the best performance out-of-the-box.
Our Instant Chatbots are trained to deal with language register variations including polite/formal, colloquial and offensive language. We have profiled the language register use in user queries from a wide range of vertical bots, and we use this information to generate training data with a similar profile, ensuring maximum linguistic coverage.
We also introduce noise into the training data, including spelling mistakes, run-on words and missing punctuation. This makes the data even more realistic, which makes our Instant Chatbots more robust to the type of “noisy” input that is common in real life.
- Retail Banking
- Events & Ticketing
- Field Service
- Legal Services
- Media Streaming
- Mortgages & Loans
- Moving & Storage
- Real Estate / Construction
- Restaurant & Bar Chains
- Retail / E-commerce
- Wealth Management
Retail Case Study
Deploying a bot which is able to engage in sucessful converstions with customers worldwide for one of the largest fashion retailers.
A Benchmark based on Dialogflow shows increased standard accuracy +40%.
See how automatic training improves manual training.
Get the full dataset used to generate the benchmark results. Check out how easy is to integrate the training data into Dialogflow and get +40% increased accuracy.
SAN FRANCISCO, USA
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