What Is A Key Differentiator Of Conversational AI

Introduction

Conversational AI uses machine learning to create speech-based apps that enable humans to communicate with machines, devices, and computers via speech. But what is a Key Differentiator Of Conversational Ai from regular chatbots.

Conversational AI is used in our day to day life when you wake up, ask for directions, or communicate with a virtual assistants like Google home, Alexa etc. for shopping or regular searching. The device can understand your normal voice and responds with natural speech. The technology behind conversational AI is complicated. It involves a complex processes with multiple steps that require a lot of computing power. Additionally, computations must be completed in real time to provide a great user experience.

In this post we will demystify Conversational AI , components ofconversational ai and what is a key differentiator of conversational ai.

Components of Conversational Ai Pipeline

The conversational AI pipeline typically consists of five components:

1. Automatic Speech Recognition (ASR).
2. Natural Language Processing (NLP), or Natural Language Understanding, (NLU).
3. Text-to-Speech with Voice Synthesis
4. Advanced Dialogue Management
5. Machine Learning (ML)

How Does Conversational Ai Works

• The application first receives information from the person. This can be written text or spoken words. ASR (also known as voice recognition) is the technology that interprets spoken input and converts it into machine-readable text.
• The application must also decipher the meaning of the text. Natural Language Understanding (NLU) is one component of Natural Language Processing. It helps to understand the meaning behind the text.
• The application then forms the response using Dialogue Management. Dialogue Management orchestrates responses and converts them into human-friendly format using Natural Language Generation, which is another part of NLP.
• The application will then deliver the response either in text or will use speech synthesis or text to speech for artificial production of human speech response.
• Lastly, we have the component that learns and improves the application over time which uses machine or reinforced learning. The application accepts corrections, and then learns from them to provide a better response for future interactions.

Example Of Conversational AI

Conversational AI can be used in various sectors.Some of the example ofConversational AI are as follows:

• Customer Service: Conversational AI bots can be utilised to offer effective customer support . They can be used to respond FAQs.  If the threshold of confidence is reached it will give the control to a person. But, it continuously learns from its mistakes to improve the quality of the response in the future to prevent such a scenario from happening. IBM Watson is one the example of conversational AI used in this sector
• Sales And Marketing: AI bots are also employed to market low-cost products by helping buyers to compare products from various sources. AI bots are also useful to market product to the prospective customer and, once it customer have shown some interest, the bot can transfer control to a person.
• Automating Tasks: One of the most powerful technological capabilities of chatbots AI bots is their ability to perform repetitive tasks. For instance, sending out messages regarding meeting times for them, setting up alarm etc.
• Virtual Assistants: The most popular uses of AI bots is that of an assistant to a person. It is able to comprehend conversations in conversation and adjusting them to a specific case or situation. Technology giants such as Apple, Microsoft, and Google are currently dedicating on AI research. R&D efforts on this application.Amazon’s Alexa, Google Assistant, Apple’s Siri are one the best example of conversational AI used in this field.
• Sales And Marketing: AI bots are also employed to market low-cost products by helping buyers to compare products from various sources. AI bots are also useful to market products to prospective customers and, once a customer has shown some interest, the bot can transfer control to a person. AI tools, including AI video editor online, can create engaging promotional videos, further enhancing the marketing strategy by showcasing products in a visually appealing manner.

What Is A Key Differentiator Of Conversational Ai?

1. Machine Learning (ML): It is a collection of algorithms, features and data that help to improve user response by analysing human agent responses.
2. Natural Language Processing (NLP ): Natural language Understanding and Natural language generation allows you to “read” and “parse” human language and generate appropriate responses back.Natural language Understanding is a prerequisite for understanding natural sentence structure and simple keyword triggers.
3. Integrations: This allows systems to execute end–to-end actions via Application Programming Interfaces (APIs), and other business operations tools. These features allow us to do more autonomous actions.

Conversational AI Vs Rule-based Chatbot

Conclusion

In this post we learn’t what really conversional ai is along with it we learn’t that machine learning(ML), natural language processing(NLP), Natural Language Understanding and its integration to understand human behaviour, this is what is a key differentiator of conversational ai.

Got a question or just want to chat? Comment below or drop by our forums, where a bunch of the friendliest people you’ll ever run into will be happy to help you out!