In general, they are not considered part of the conversational AI system, but work closely together to satisfy the user’s needs. The fulfillment engines execute the tasks that are functional to the conversational AI system, for instance: retrieving weather information, reading news, booking tickets, providing stock market information, answering trivia Q&A and much more.The dialog manager takes information from the NLU module, remembers the context, and fulfills the user’s request. A dialog manager monitors the state of the conversation and decides which action to take next.NLU is part of natural language processing (NLP), a subfield of linguistics and artificial intelligence concerned with computational methods to process and analyze natural language data.A natural language understanding (NLU) module parses the text and identifies relevant information, such as the intent of the user, and any relevant parameter to that intent. For example, if the user is requesting, “What’s the weather tomorrow morning?”, then “weather information” is the intent, while time is a releva,nt parameter to extract from the request, which is “tomorrow morning” in this case.A dialog system manages the conversation with the user while interacting with external fulfillment systems to satisfy the user’s needs.A speech interface, enabled by speech AI technologies, enables the system to interact with users through a spoken natural-language format.The components of a typical voice-based conversational AI system include the following: The relationship between AI, ML, DL, and speech AI can be represented by the Venn diagram in Figure 1.įigure 2. Speech AI is a subfield within conversational AI, drawing its techniques primarily from the fields of DL and ML. This turns a text into a verbal, audio form.
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