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Oracle introduces natural voice conversations to Digital Assistant

Now, enterprise customers can use voice commands to communicate with their enterprise applications to drive desired actions and outcomes, enriching the user experience with conversational AI

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Oracle has announced availability of its AI-trained voice with Oracle Digital Assistant. Now, enterprise customers can use voice commands to communicate with their enterprise applications to drive desired actions and outcomes, enriching the user experience with conversational AI, simplifying interactions and improving productivity.

“Enterprises are demanding an AI-powered voice assistant that understands their specific vocabulary and enables naturally expressive interactions for its users,” said Suhas Uliyar, vice president, AI and Digital Assistant, Oracle.

Digital Assistant applies AI with deep semantic parsing for natural language processing (NLP), natural language understanding (NLU) and custom machine learning (ML) algorithms. This combination allows Oracle Digital Assistant to understand a user’s natural conversation, derive intent, produce compositional logical forms, and identify and learn user behavior patterns in order to proactively take action on behalf of the user. A no-code tool that allows enterprises to build conversational experiences, the voice-enabled solution can also integrate with human agent work-flows and business processes without any coding required.

Oracle’s intelligent voice assistant for the enterprise brings conversational AI to new applications by analyzing enterprise-specific and domain-specific vocabulary on which open and consumer-oriented domain models are not trained on. Oracle Digital Assistant, the only enterprise digital assistant on the market today, makes voice and user interactions more expressive by processing complex queries and deriving intelligence from all available enterprise applications, such as ERP, CRM and HR systems to respond in the context to the request made.

The NLP engines that power today’s traditional messaging-based channels lack the ability to handle highly expressive sentences. Voice interactions, however, enable expressive conversations which require NLP engines to manage much more complex constructs. Linguistic constructs like relative clauses, comparatives, superlatives, negation, anaphora, ordinals, cardinals, superlatives, ellipsis, quantifiers and conjunctions now need to be processed by the NLP engines that require more sophistication than the simple intent classification and slot-filling engines available today.

Oracle Digital Assistant NLP now comes with a semantic parser that understands these complex linguistic constructions and produces compositional logical forms that go beyond slot-filling. A sales key account manager can, for example, use Oracle Digital Assistant to schedule a lunch meeting with the Key Account Director or “KAD” and locate the most convenient parking garage for the meeting. Asking the Oracle Digital Assistant to “Find the address of the closest parking garage near the Japanese restaurant by Japantown’s Peace Pagoda” will return directions to the nearest parking garage not the Japanese restaurant. In addition, the acronym “KAD” is a contextual and enterprise-specific term which consumer-grade voice systems typically misinterpret. Oracle Digital Assistant is uniquely able to distinguish enterprise- and domain-specific vocabulary that various HCM, ERP and CX systems use regularly.

Oracle Digital Assistant is pre-built with AI-trained enterprise skills across ERP, SCM, HCM and CX and can connect to multiple back-end systems simultaneously to orchestrate user interactions across various application skills. With these plug-and-play skills, line-of-business users only have to interface with one digital assistant that can source the right information from employee directories, expense management systems or an assortment of other enterprise applications, including Oracle Cloud Application offerings. Oracle Digital Assistant can also be deployed to popular conversational interfaces, such as Microsoft Teams, Slack, Facebook Messenger, WeChat and across voice interfaces like Siri and Alexa.

 


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