Using artificial intelligence to synthesize texts provides numerous advantages for contact centres. AI enables key information to be extracted and rephrased quickly and easily.
Thanks to natural language processing (NLP), AI can produce two types of summaries: extractive and abstractive. The summary produced can be limited in terms of sentences or words, according to the parameters that the user has predefined in the tool.
Extractive summarization selects sentences representing the most relevant information from the original content. This technology identifies and extracts the essential sentences from the original unstructured text. In concrete terms, when you request a three-sentence summary, the tool returns three sentences from the document which are the best evaluated, i.e. which best reflect the general idea of the text.
Meanwhile, abstractive summarization captures the main idea without necessarily using the same words as the original text, a feat achieved through Generative Artificial Intelligence. Abstractive summarization generates a shortened text that doesn’t necessarily contain the same words as the original text, but captures the main idea. The resulting summary may differ in terms of vocabulary, but presents all the important ideas.
By combining the extracted information, AI produces augmented summaries that provide a global view of customer interactions, and enable you to detect potential malfunctions in the contact center.