Noisy text is realistic text

[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"

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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.

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Linguistic Resources in +100 Languages & Variants

[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

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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.

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Some figures on chatbots and eCommerce

[fa icon="calendar'] Dec 31, 2019 2:30:00 PM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLU, AI, Multilanguage, NLP for Chatbots, "Multilingual synthetic data", aws

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When we talk about the usefulness of chatbots, we sometimes look at it as a black or white matter. Yet, the issue is not whether chatbots are useful or not, it’s rather how useful they are, and whether it is worth keeping them.

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Bitext’s Customer Support Dataset for free

[fa icon="calendar'] Dec 26, 2019 5:15:00 PM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLU, AI, Multilanguage, NLP for Chatbots, "Multilingual synthetic data", aws

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We have shown in previous posts why Synthetic Training Data is the best way to boost the accuracy of any chatbot, and the solution to the most important problems of chatbots nowadays: data scarcity, namely, the lack of accurate and useful training data for the problems chatbots want to address.

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Amazon Connect: the new step into chatbots

[fa icon="calendar'] Dec 24, 2019 5:00:00 PM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLU, AI, Multilanguage, NLP for Chatbots, "Multilingual synthetic data", aws

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Do you know Amazon Connect? It’s a new platform created by Amazon —and built on AWS— that allows you to have your own Contact Center in the cloud, without having to get all the infrastructure that usual contact centers need. The philosophy is “Contact Center as a Service”, and Amazon is not the only one to implement it, but it’s actually one of the most interesting ones.

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Bots that save you money

[fa icon="calendar'] Dec 20, 2019 1:00:00 PM / by Bitext posted in Machine Learning, NLP, Big Data, Bitext, Deep Linguistic Analysis, Natural Language, Text Analytics, Artificial Intelligence, Deep Learning, Chatbots, NLU, AI, Multilanguage, NLP for Chatbots, "Multilingual synthetic data"

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A few days ago we talked about how chatbots didn’t prove to be the revolution many of us expected. As we saw, one of the problems was related to expectations: chatbots were expected to be a magic wand that would solve everything. Yet, this doesn’t mean chatbots are not extremely useful when applied in the right environments and with the right goals in mind. We’ll present some cases of useful chatbots in the next weeks.

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