What is the Difference Between Chatbot applications and a Virtual Assistant devices?

Answering the queries of the humans now possible with automated machines like chatbot application or virtual assistant devices. Both are trained through machine learning algorithms to work like an AI based system but there is a difference between these two and you can find here with right examples.

What is Chatbot?

Chatbot is an application answer the questions or solve the queries of different people on a particular topic, field or area. Means, a chatbot can answer the queries within specific topic not beyond that, and it gives various options while answering the questions. Chatbot is basically, used by the companies as virtual assistant customer support service to assist their customer and resolve their queries.

What is Virtual Assistant?

A virtual assistant is also answer the questions of the people but it can talk about different topics from different fields. From weather report to current news headlines and various other updates, can be taken by asking from virtual assistant devices. Alexa, Google Assistant, and Siri are the leading virtual assistant devices used by the people globally get the answers on various questions or perform various tasks.         

How Chatbot is Different from Virtual Assistant?

Chatbot can answer only queries on specific topic, products and services related queries, while virtual assistant can perform multiple tasks like telling weather condition, setting alarm, playing songs and making calls etc. on voice based command spoken in the native language.

Chatbot basically, designed to answer the questions either given by written texts or within predefined related questions and answers. While on the other hand, a virtual assistant devices interact with people through voice command. Anyone can ask the question in any human language and it will give the best suitable answer either from its database or after searching from the internet.

How Chatbot and Virtual Assistant are developed?

Both are machine learning based applications but you can say virtual assistant is more AI-enabled device, as it can also learn from people how they ask questions and get the feedback to improve its performance. While chatbot is not so intelligent, except giving the answers from is pre-stored database.

To develop both Chatbot and Virtual Assistant machine learning based technology is used. A huge amount of training data sets are used to train the algorithm learn how to answer the various questions of the different people when asked on specific or various topics.

While virtual assistant also get language based varied big data sets containing not only understanding the language and ascent of people use while speaking with such devices. The data is precisely annotated to make it comprehensible to algorithms and helps the virtual assistant device give the most suitable answer in different languages with best level of accuracy.

Types of Training Data Sets Used in Chatbot & Virtual Assistant Development

In chatbot training only topic specific training data is used to train the model, while in virtual assistant, apart from various topics, there are multiple things the model need to train like understanding the ascent of asking the question, different languages and topics to give the most accurate answer.

Texts, audio, speech, sound and language other data sets are labeled with precise data annotation techniques to make them comprehensible with best level of accuracy. Chatbot training data contains the annotated texts or audio sounds that are earlier answered while answering the queries.

Cogito provides, the Chabot training data for such applications and high-quality training data sets for virtual assistant training. It can annotate or label the data with right techniques for right machine learning. Cogito can deliver the natural language processing training data with text, audio, named entity annotation and relationship extraction for machine learning and AI development.

Source

Roger Brown

Cogito Tech is the industry leader in data labeling and annotation services to provide the training data sets for AI and machine learning model developments. All types of AI and ML services requires the training data for algorithms with next level of accuracy making AI possible into diverse fields like healthcare, gaming, agriculture, retail, automotive, robotics and security surveillance etc.

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