“How may I assist you?”
“What are you looking for?
Does the right corner of almost every website that you open look like this? It’s your personal assistant speaking to you. Here we will talk about chatbots, the trending online interactions agents, and chatbot training data services.
With technology entering almost every sphere of human life, chatbots have become a thing and probably one of the most common formats of reinforced learning that humans are interacting with on a daily basis. Witnessing the time spent by consumers on messaging platforms, brands are turning to these messaging platforms to better interact with consumers. These chatbots represent a flourishing trend in online interaction both for brands and users – brands to quickly provide information to customers, and users to jump straight to the point without needing to hang on to a message or FAQs.
Today, the most widely used chatbots are likely the AI assistants from industry players such as Alexa from Amazon and Siri from Apple. Chatbots are the assistants that streamline interactions between customers and services while enhancing consumer satisfaction and experience.
From the business point of view, integrating a chatbot can prove to be extremely beneficial. From promoting customer satisfaction to streamlining interaction between customers and services to saving the costs of hiring a huge team of customer support, the advantages of integrating and training a chatbot are ample. This brings us to the different types of bots that are available.
Not all bots are the same; each serves a different purpose, handles data in different ways, and has different ways of simplifying the way businesses interact with their customers.
- Entertainment Bots: These types of bots interact with users for a long period of time. They can either be assessed with a Turing test or by analyzing quantitative metrics such as the time spent by a user with the bot or the length of the conversation.
- Enterprise Bots: Their prime focus is on the user’s needs and demands. In other words, they have a specific purpose to serve or a goal to achieve. The conversations that happen here are usually short and precise.
- Scripted Bots: As the name suggests, these bots are scripted i.e. they can offer only a limited set of functions or cater to limited questions and accept only a narrow range of responses.
- Machine Learning Bots: These are the bots that expand their knowledge and understanding by studying the previous chats or watching live conversations and learning from these over time.
Now that we know the types of chatbots, the question is, how do the bots learn?
Well, just like we, humans, need the training to perform professional activities, so do chatbots. Chatbot training data services enable your AI-based chatbots to interact with real-life users by understanding, remembering, and recognizing different types of user queries while providing relevant answers and explanations.
Before we know how chatbots learn, let’s have some basic knowledge of chatbot training services.
Chatbot Training Data Services
Training data is quintessential for conversational AI/ML-based models like chatbots. Different chatbots need training for different interaction skills and this is where professional chatbot training data collection services come into the picture. These services can help you prepare your chatbot model to recognize text/voice messages and accurately respond to them while following the conversational protocols.
Humans have different ways of expressing themselves. From excitement to grief to anger to happiness, the tones in which humans express can be understood by other humans easily, however, chatbots are not familiar with these tones and must be trained for the same. Chatbot training services use various multilingual datasets to train chatbots so that they can identify the tone/ theme of the message correctly.
Just like tones, intent may vary. Chatbot training experts categorize user utterances into relevant, predefined intent categories and design chatbots for a particular use case to help the chatbot in understanding and recognizing different intents with the same meaning.
Thanks to rich and diverse human languages, interactions are often complicated. People who belong to different demographic groups have different ways of expressing the same sentiment/intent. Thus chatbots have to be trained to discover the common intent. This is done with the help of diverse training datasets to help chatbots detect the different ways people express the same intent and respond accordingly.
According to Chatbots Magazine, smarter chatbots using NLP must be capable of carrying out the following functions:
- Summarization: Ability to summarize large amounts of text into a short, concise explanation.
- Open and closed questions: Able to answer all sorts of questions, whether open or close.
- Conference: Able to relate objects with words by connecting to previous conversations.
- Ambiguity: Able to correctly associate the meaning with the word
- Morphology: Able to separate words into individual morphemes.
- Semantics: Able to translate any human natural language, whether it’s for creating a response or analyzing questions.
- Text Structure: Make the correct use of punctuation, spacing, or text.
- Sentiment: Detect the emotional polarity of the subject the human is talking about.
Despite the advanced options, chatbots can run on simple ML models as well. They can be trained to respond to distinct questions with predetermined responses. You can further classify them within different categories of responses as and when new questions come in.
However, including the mentioned functionalities is always a good idea to make your chatbot unique and advanced. You could also ask chatbot training experts to include these functionalities in your chatbot model.
Train The Bot For Natural Language Processing
This element is one of the most vital layers of any chatbot. Without a Natural Language Processor, human language communication between a man and a machine isn’t possible. NLP, basically, refers to the components that allow the chatbots to conduct a conversation that’s nearly identical to human interaction. NLPs study human input with the help of deep learning and generate a human response(s) accordingly.
Machine learning bots are fed a set of data to warm them up before placing them on the battlefield. NLPs, with the help of a declarative approach, promote intent and entity recognition where various example sentences guide the bot about the terms that are important in the conversation and what users are trying to achieve.
Once up and running, bot builders, with the help of analytics from the conversations, can detect the problem areas and accordingly add critical new example sentences for the best results.
As time passes, smart bots gain more knowledge and expand the range of features they offer while proving to be more valuable for businesses. The smarter they are, the more businesses can save time and ultimately revenue.
Also, as AI becomes smarter and prevalent in bots, they can continuously learn and improve the services they offer while constantly serving customers with relevant and helpful answers. However, no matter how trained your bot is, you must keep a check on user interactions to ensure it is meeting your needs and solving customer’s queries.
Are you ready to take on the chatbot training drive with SunTec.AI?We provide you with exceptional, relevant data-sets to train your chatbots for them to solve customer queries and take appropriate actions as and when required. Our chatbot training experts have industry-best experience and skills in gathering, categorizing, and processing large volumes of data. Discuss your chatbot training requirements and know more about our chatbot training services by contacting us at firstname.lastname@example.org.