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  • Conversational AI

Conversational AI Services

Engaging | Intelligent | Personalized

Conversational AI

Conversational AI Services

Engaging | Intelligent | Personalized

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Trending

Human-machine interaction has come a long way since the inception of interactions of humans with computers. Breaking loose from earlier clumsier attempts at speech recognition and non-relatable chatbots; we’re now focusing on perfecting what comes to us most naturally—CONVERSATION. 

Conversation bot design is the most happening thing when it comes to AI computing and an essential thing to consider for making products smart and digitally inclusive. With the rapid progress in AI and specifically in NLP computing, language interpretation has improved considerably, making a near-normal conversation possible since the time Siri was first introduced in iPhone 4s in 2011.

Today we see, chatbots have proliferated as part of the web application extensions. Adding a voice or chat interface is the fastest way to qualify an application AI-ready, the chatbot is also the strategy for the mobile-first digital economy. Natural Language (Conversation) interface is the preferred mode of intelligent interaction between humans and the technology they use, own, and wear. Consumers want to use everyday phrases, terminology, and expressions to control apps, online services, devices, cars, mobiles, wearables, and connected systems (IoT). And they expect quick & intelligent responses.

Consumers today highly value quick and efficient communication; Currently available slot-filling chat-bots which are at some point of time non-relatable and frustrating at the worst do not fit the bill. For such cases, these are the most important characteristics sought in terms of conversational AI/bots: Multilingual Conversational Engines, Human experience to any interaction, Context-Aware & Intuitive, & Response Adaptation as per Customer Sentiment.

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Opportunities & Challenges

Opportunities & Challenges

Opportunities & Challenges

Evolving consumer behavour and proliferation of digital connected technologies are propelling customer centric services and products to the fore. As per reports 84% of companies who focus on improving customer experience are reporting an increase in annual revenue. 

Engaging and successfull conversations are the most important factor in enhancing customer experience. Successful conversations that engage customers for longer durations require a good understanding of intent and sentiments; this can be challenging without the use of deep learning technologies and neural networks.

The existing voice assistants still have mundane responses, you need to understand the technology like framing questions in a certain predetermined format, usage of predetermined or programmed keywords, etc. A simple combination of tasks like “Turn on the AC and lock the car” is still a challenge for the bots to comprehend and execute. Besides, present-day bots are unable to derive context or retain context from previous conversations with the same user.

To build an intelligent Conversational Agent, understanding user intent is key. There are many parts to this challenge, too many variables to solve. Human comprehension of language is complex, and not everything of it is verbal. As human listeners, we consider many things like the speaker’s facial expression, hand, and body movement, which is also called ‘body language that is unfortunately not under the purview of the NLP computing domain. Language understanding has the following key parts, and each of them needs to be solved separately to figure out the holy grail:

  • Understanding semantics (lexical)
  • Understanding syntax
  • Understanding context (both short and long term)

Service Framework

Conversational AI
SymanTEx: Platform as a Service
  • Platform for Omnichannel intelligent communication systems
  • Voice Interface with Conversational Touch
  • Dialogue Bias as per Idiolect
  • Intent & Sentiment based Context Awareness
  • Domain Agnostic Neural Network Architecture
  • Speech Recognition & synthesis 
  • Multi lingual ASR and speech synthesis system
Service Features
  • Voice Biometrics
  • Sentiment Analysis
  • L1 & L2 Support automation using voice bots
  • Voice Cloning & Speech synthesis
  • Virtual Buddy
  • Auto Transcript

Differentiators

  • Natural Language Understanding using proprietary Deep Learning Neural network
  • Context-Aware Intuitive Conversational Interface
  • Quick, Relatable, Personalized, and Efficient 
  • Lighter footprint ASR system optimizable to deploy on embedded platforms
  • Generic “Voice-Based” Framework
  • Lego block concept

 

 

Benefits to the Customer

  • Faster product launch
  • Efficient resource usage based on SymanTEx
  • voice or chat-based conversation engine for any given context
  • Multilingual Conversational Engines
  • Human experience to any interaction
  • Context Aware & Intuitive
  • Response Adaptation as per Customer Sentiment

Tata Elxsi's Artificial Intelligence Centre of Excellence
Perspective

Tata Elxsi's Artificial Intelligence Centre of Excellence

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