In this blog we will discuss three ways of doing your chatbot evaluation by using:
- real world evaluation data
- synthetic data
- "in scope" or "out of scope" queries
[fa icon="calendar'] May 31, 2021 10:00:00 AM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLU, POS tagging, AI, Multilanguage, NLP for Core, NLP for Chatbots, "Multilingual synthetic data"
In this blog we will discuss three ways of doing your chatbot evaluation by using:
[fa icon="calendar'] May 25, 2021 5:00:00 PM / by Bitext posted in API, Machine Learning, NLP, Big Data, Bitext, Natural Language, Artificial Intelligence, Deep Learning, Chatbots, Phrase Extraction, NLG, TechCrunch, NLU, AI, Multilanguage, NLP for Core, NLP for Chatbots
Chatbots can improve customer experience in contact centers by:
Most customer service and contact center executives are honing in on bots because they can handle large volumes of queries. Thus, their service center staff can focus on more complex tasks. As the technology behind bots has improved in terms of natural language processing (NLP), machine learning (ML), and intent-matching capabilities, companies are increasingly willing to trust them to handle direct customer interaction.
[fa icon="calendar'] May 11, 2021 5:52:38 PM / by Bitext posted in API, Machine Learning, NLP, Big Data, Bitext, Natural Language, Artificial Intelligence, Deep Learning, Chatbots, Phrase Extraction, NLG, TechCrunch, NLU, AI, Multilanguage, NLP for Core, NLP for Chatbots
The following practices will help you design a great conversation between your chatbot and your client:
Reducing complicated, confusing processes down to a natural conversation is potentially a huge business opportunity for anyone willing to jump headfirst and create a great user experience. Chatbots are only as smart as the words you feed them. If a bot is too rudimentary, people will lose trust in the company and will feel ignored and unappreciated. UX problems appear when the user deviates from the designed linear flow.
[fa icon="calendar'] Nov 16, 2020 7:15:12 PM / by Bitext posted in Machine Learning, NLP, Bitext, Natural Language, Artificial Intelligence, Deep Learning, Chatbots, NLG, Multilanguage
[fa icon="calendar'] Feb 24, 2020 4:45:00 PM / by Bitext posted in API, Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, NLG, NLU, Query Rewriting, AI, Multilanguage, NLP for Core, NLP for Chatbots, NLP for CX, "Multilingual synthetic data"
One of the flaws of usual training data generation is that, when you ask somebody to manually create training data for you, they will make an effort to write these sentences correctly, following the spelling and punctuation norms of your language. Even if some errors appear, they will be minimal, because they are trying to do things right —this is, to provide “orthographically right” sentences.
[fa icon="calendar'] Feb 11, 2020 2:55:24 PM / by Bitext posted in API, Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, NLG, Stemming, NLU, AI, Multilanguage, Language Identification, Decompounding, Lemmatization, NLP for Core, Finance, Banking
All Machine Learning (ML) engines that work with text can benefit from a solid linguistic background. If they are working in a multilingual environment, the need of a good lexicon (with forms, lemmas and attributes) is overwhelming. Even so, basic features such as Word Embeddings hugely improve when enriched with linguistic knowledge, and if this is not usually applied, is because of a lack of linguists working for ML companies.
Bitext delivers the most precise and granular text analytics solution on the market, with an accuracy rate above 90%.
We are computational linguists first. Our technology really understands sentence structure and its different layers of meaning, so it always produces the richest results.
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