The use of word embeddings has become the standard approach for dealing with text input in AI models. While an extensive research has been carried out during these years to analyze all theoretical underpinnings of algorithms such as word2vec, fastText and BERT, it is...
In recent years, word embeddings have become the de facto input layer for virtually all AI-based NLP tasks. While they have undoubtedly allowed text-based AI to advance significantly, not much effort has gone towards examining the limitations of using them in...
Almost three years after Apple launched its well-known voice assistant Siri for the Arabic language, there is still room for further improvement. Siri can currently understand more than 20 languages and dialects; but, when it comes to Arabic, its abilities are not...
Bots built upon machine learning need long training processes to have the ability to hold a meaningful conversations with real people. Training data becomes, therefore, a diamond in the rough; all companies need such input for their bots. Until now, this data was...
Increasing bot accuracy has never been so easy. How? Generating artificial training data, not manually, but using auto-generated query variations. We have benchmarked Rasa and other platforms, and their accuracy comes up to a 93% thanks to Bitext artificial training...
The well-known Rasa chatbot-building platform is gaining weight day after day. But, in all platforms, chatbots are as good as their training material. Rasa, as other chatbot platforms, still relies on manually written, selected and tagged query datasets. This is a...
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