Year: 2021

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Which Data Annotation Companies are Best to Provide NLP and Transcription Services ?

Data annotation companies are basically involved in annotating the different types of data available in the various formats like text, images and videos etc. And the data annotation process is done to create the training datasets for machine learning and AI model developments.

Data Annotation Companies

Labeling the data with added metadata or notes becomes useful for machine learning algorithms. Similarly, images are annotated to make various types of objects recognizable to machines through computer vision technology.

And there are many data annotation companies offering this service for AI companies as per their training data requirements and affordability. Cogito is one of the data annotation companies offers the image annotation services for different types of machine learning and AI models.

Natural language processing services

The language or voice based AI models need the data that can help the algorithms understand the communication process and language used to communicate between the humans. Hence, Natural Language Processing Services helps machines learning acquire only the useful words from the sentence and make it understandable for AI word through annotated language.

Data annotation companies also provide NLP annotation for all types of language based AI models. Cogito is the right platform for the AI companies to bridge this gap by employing natural language processing annotation solution for wide-ranging needs like speech recognition, sentiment analysis, virtual assistance and chatbots.

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1. How Conversational AI can Automate Customer Service

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Transcription Services

Converting the information from one format to another format sometimes important for different needs. Transcription is the right process to convert the content from one format to another format. Audio, Video and OCR Transcription is the most popular transcription services used to transcribe the data from one format to another without losing the essence of the entire information.

Cogito is the data annotation company but also provides the transcription service to transcribe the data from one format to another format with best level of accuracy. It can transcribe the audio or video in any language to written text or other desired formats while ensuring the privacy of the data. OCR transcription with end-to-end data handling service offered by skilled professionals at Cogito.

It is one the well-known data annotation company providing the annotation service and transcription service as per the customize requirements. It can annotate any type of data including NLP with ability transcribe the information from one format to another format with extra precision.

Don’t forget to give us your 👏 !

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Which Data Annotation Companies are Best to Provide NLP and Transcription Services? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

In this age of digital transformation where businesses are moving to digitize and automate many operations, chatbots and various cognitive virtual assistants are being highly adopted. Not only is customer service, but they are quite useful in internal operations as well. However, the actual difference between them is poorly understood.

The confusion is not completely people’s fault as both chatbots and virtual assistants have been developed during the same time but while marketing and reaching out, weren’t explained to people well.

Many people tend to use these words interchangeably which, on a small scale, might not cause big errors but would definitely cause some in the long scale and in some specific use cases. Using chatbots in cases where you actually need virtual assistants would not satisfy you fully and provide disappointing results while using virtual assistants in cases where chatbots are sufficient would be overkill.

In this article, let us compare chatbots which are intelligent virtual assistants in various aspects so as to understand the differences of both. By end of it, you would have a good understanding of chatbot vs virtual assistant and will help in making a decision as to what works best for you.

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1. How Conversational AI can Automate Customer Service

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3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Use Case

Chatbots and Intelligent virtual assistants are designed and developed with different intents and purposes. The use case is a primary cause of confusion between chatbots and intelligent virtual assistants.

On the surface, both use cases of chatbots and virtual assistants match, like automating customer experience, automating certain business use cases, and more. However, it only becomes clear when you go down in detail.

Chatbots are used in cases where you want to give small details to users or have a general chat with them. It might be getting them a FAQ or just answering small queries and taking action and when it could not, transferring to sales executive. Here, chatbots typically do not retain context(which we would discuss later in this article).

Virtual assistants are used in cases where a higher degree of assistance is needed to be given to users regarding various aspects and also, there must be higher retention of data.

For example, if domain and context are very tricky where small changes in words might cause huge changes in meaning and complex actions are required for a correct conversation experience, intelligent virtual assistants are the way to go.

An application must be able to handle complex sequences of actions without actually contacting representatives…, virtual assistants are used.

Technical Sophistication

This, again, is a source of confusion. Both software of chatbots and intelligent cognitive virtual assistants use technologies of Machine Learning, Artificial intelligence, and derivatives of them like Natural Language Processing, speech recognition, and more. However, the way in which they are used and to what depth they are used vary.

Basically, both use trained machine learning models on large data sets, but intelligent Virtual chatbots use cognitive AI which is more advanced than AI used in chatbots. As such, even the best chatbots might not be as capable as a good cognitive virtual assistant.

While both chatbots and intelligent virtual assistants learn from chats, cognitive learning virtual assistants can better learn more data and gain more insights than a chatbot application.

Intent Understanding

Whether for chatbots or virtual assistants, understanding the user’s intent is a very crucial step. Intelligent Virtual Assistants are better equipped to understand the intent of the user than chatbots. Compared to virtual assistants, chatbots cannot differentiate little nuances in user’s requests to process their intents.

Chatbots also cannot easily handle disambiguations and provide a straight answer even when an intent is originally unclear but a best virtual assistant would be well able to handle all disambiguations and ask for further clarification. Also, virtual assistants are way better than understanding various spelling mistakes where they would have various models of spell errors including qwerty errors, phoneme models, and more.

Also, purely trying to detect raw intent is also not appropriate for all cases. Consider a case in which user exhibits certain emotion like they are feeling sad today and want to do something, a chatbot would give a straight reply but an intelligent virtual assistant would provide an extended answer.

Retaining Users’ Context

Not all times user’s requests are complete in a single instance of chat and their context needs to be carried forward. General chatbots do not contain technology to retain the user’s context but cognitive virtual assistant AI would store the user’s context and tailor the responses based on context.

Setup and Initial Investment

Chatbots tend to have a very easy setup and little initial investment in terms of specification because they are simple. On the other hand, intelligent cognitive assistants need much more information and thus, need considerable initial investment in terms of defining use cases, providing more examples, and more.

Price

As chatbots and virtual assistants differ so much in technical sophistication and capabilities, there would naturally be a difference in price.

Just as many software products these days, chatbots and virtual assistants are available in many tiers wherein each tier you would get more and more features and a custom plan where you create a personalized plan.

The price difference between chatbots and virtual assistants would be so much so that the high tier price of chatbots tends to match the basic tier price of virtual assistants!

Final Words

So, by now you may have well understood that chatbots and virtual assistants may overlap in use cases generally but differ a lot. Chatbots are useful for providing basic conversational experiences that are relatively easy to set up and cheap. Intelligent Virtual assistants provide powerful and complex conversational experiences that are able to handle requests more efficiently and give the most appropriate responses. However, they can have a relatively complex initial setup and are expensive.

So, based on your context and use case, go for the most appropriate solution!

Don’t forget to give us your 👏 !

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Chatbots vs Intelligent Cognitive Virtual Assistants was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Search Engine Optimization or SEO is one of the essential aspects that can impact your website traffic. It is a process that allows your website to rank higher in the Search Engine Result Pages(SERP) and attract more visitors. According to BrightEdge, SEO drives 1000X more traffic than organic social media. So, it is not an aspect you want to miss out on, but can a chatbot make any difference?

Chatbots have been the innovation that has amalgamated advanced technologies like Artificial Intelligence, Natural Language Programming, and Machine Learning. Engaging your audiences is essential to SEO, and chatbots have enabled different ways of engagement like usage for purchases, meeting scheduling, or mail list sign-ups.

However, enhanced user engagement is just one of the many benefits that you can get by developing chatbots for your website. Here, we will discuss the advantages of chatbots for SEO and how to create one for your website? So, let’s not waste time and start right away!

Top Benefits of Chatbots for SEO

SEO is one of the most effective tools to market your services or products. As per a survey, about 50% of marketers believed that SEO could boost digital marketing campaigns. However, SEO success is not easy to achieve as there are several parameters involved.

Source: http://www.marketingcharts.com/online/which-digital-marketing-tactics-are-perceived-to-be-the-most-effective-and-difficult-66370/attachment/ascend2-effective-difficult-digital-marketing-tactics-mar2016/

Enhanced engagement, customer support, and even personalization are some of the most significant parameters that affect SEO. But, at the same time, a chatbot offers much more than just engagement and personalizations. Let’s discover!

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#1. High Availability

Whether you are a B2C business or B2B, offering 24/7 customer support is one of the most significant parts of your services. According to the studies, most customers expect companies to be available 24/7. Higher availability of customer support means that your users have the convenience of communicating at any time. In addition, faster resolutions mean better customer satisfaction.

#2. Right Resolution

Chatbots can help in delivering not just faster but the suitable resolutions. These intelligent programs are explicitly designed to resolve the problems that customers have with the services and products. SEO rankings are based on several different elements.

For example, websites with higher bounce rates can hurt SEO rankings. Bounce rates measure the percentage of users that leave a webpage without taking any action like filling a form or clicking a CTA. The best way to reduce bounce rate is by offering the content or solution that a user is looking for while visiting a website.

A chatbot can have conversations with the users through innovations like Natural Language Programming(NLP) and speech recognition. It allows chatbots to understand what users want and offer the exact content or guide them to the proper resolution.

#3. Customer Journeys

Businesses can enhance customer journeys through chatbots. One of the essential parts of the customer journey is onboarding. Your customers may know the product and even the services while interacting with your systems, but allowing them to be familiar with different functionalities can make a massive difference.

This is where the chatbots can act as a guide to the customer’s onboarding process. Enhanced customer journey means better traffic and lower bounce rates leading to better SEO.

#4. Personalizations

Personalization of services is essential to businesses and SEO. Chatbots can offer personalizations by gathering data from the users during the interactions and Machine Learning algorithm to offer recommendations. Take an example of the Jewellerybox. It is a jewelry brand that leveraged AI to increase the 80% of internal linking on their website and improve SEO.

#5. Higher Visibility

Chatbots can enhance SEO and improve the visibility of websites through better search engine rankings. One of the critical parameters for SEO is user engagement. Chatbots can be integrated into social media platforms and messengers to offer excellent user engagement. Due to higher user engagement and multichannel presence, the visibility of your website will increase.

Now that we have some idea why developing a chatbot for your website can be beneficial to SEO let’s discuss how to create one?

Chatbot for SEO: How to Develop?

Developing a chatbot for your website is not easy, and it gets overwhelming due to several options for APIs and libraries. From the interface to backend architecture and even the algorithm that will enable intelligent functions, many things are to be figured before developing a chatbot. So let’s begin with the design of a chatbot.

Chatbot Design

Chatbot design depends on different factors, and one of them is the complexity of the function you want to execute. There are two primary criteria for developing an AI-based chatbot,

1. Work Complexity
2. Data Complexity

Work complexity relates to the business logic and how complicated it is, and at the same time, data complexity relates to informational structure. So when you design your chatbot solution, work complexity and data complexity are essential considerations. Once you have the chatbot core design ready next important step is to create a robust architecture.

The Architecture

If you are planning to enhance the SEO of your website, the best architecture for chatbots will assist the optimization process. A hybrid architecture is a great way to build a chatbot. Such architecture has three major parts,

• Cloud Network
• Public Network
• Enterprise infrastructure

Cloud Network- The cloud network will include the heart of your chatbot- an algorithmic model. You can leverage ML algorithms to create a programmable chatbot core. The first step towards creating an algorithmic model is to prepare the data for training. Then train the model according to cumulative data. Finally, the model is tested for practical functionality and then deployed.

Enterprise Infrastructure- It includes enterprise API services that help interact with the chatbot algorithms and users through the interface. The infrastructure also has a shared repository that will accumulate content from enterprise systems. However, the most vital of all is business processes that help execute the logic designed to serve customers. It also enables integration.

Public Network-A hybrid cloud architecture will have public networks and VPC or Virtual Private Network. VPC is your cloud network where the algorithmic model resides. The public network will act as a data resource where information from social media channels, multi-media channels, and other sources are stored. It also enables API integration to third-party services like CRM software, payment gateways, and others with the chatbot algorithm.

Source:https://www.ibm.com/cloud/architecture/architectures/cognitiveConversationDomain/reference-architecture/

All these significant elements need a reliable connection to execute the chatbot function, and that is where APIs come into the picture.

API Development

APIs are essential for your chatbot integration in the website. Take an example of an engaging element like exit popups that work as a means to ask your customers to either download, subscribe, or buy a service. You can use such popups to redirect customers leaving your website to chatbots that help reduce bounce rates by keeping the user engaged.

However, integrating a chatbot redirection with a UI element like popup needs a customized API that allows interaction between the frontend and backend of the algorithm.

Conclusion

There are more than 1.7 billion websites on the internet, with an average of 57600 new ones published per day. So, the competition is cutthroat, and you need a chatbot solution that can help your website not only achieve better SEO but stand out. However, what type of chatbot solution suits your project will depend on the data complexity and specific business requirements.Don’t forget to give us your 👏 !

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Chatbots for SEO: do you need one for your website? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Welcome back to “Lessons from Our Voice Engine,” where members of our Engineering and Speech Tech teams offer high level insights into how our voice engine works.

Lesson 2 is from Lora Lynn Asvos, a Computational Linguist on our Speech Tech team.

What are CLMs?

CLM stands for “custom language model.” As mentioned in Lesson 1, language models are statistical models of language that can predict the next word based on the context.

CLMs are language models, as the name implies, but they have a little something extra. Instead of focusing generically on a given language, a CLM focuses on a specific domain of that language. This domain could be fairy tales, fables, scientific texts, cooking recipes, knitting patterns, you name it.

Even though CLMs specialize in a particular domain, they are still bolstered by general language knowledge. This allows CLMs to cope if the user goes outside the intended domain, which is particularly useful with children — they excel at saying the unexpected!Why are CLMs important for our kid-specific voice engine?

We often get this question from clients in conjunction with, “Why is a CLM better than a generic LM?” Generic LMs cover many topics and contain lots of data. For general knowledge applications, they can be useful. However, generic LMs are trained on adult words, use cases, and sentence structures. Their strength is also their weakness. As the old adage goes, a jack-of-all-trades is a master of none. Or in this case, a jack-of-all-domains.

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1. How Conversational AI can Automate Customer Service

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When a child says “the train went choo-choo,” a generic LM might interpret “choo-choo” as “to you” or “chew chew,” similar-sounding but more standard words. Children’s texts are also full of fun and unique character names, places, and objects. With a generic LM, the unique word won’t be understood, leading to a disappointing reading experience.

Since our focus is children’s speech, our CLMs are trained on kid-centric data, which means words like “choo-choo” are correctly understood. Our CLMs also allow for phrases with unique words like “the alien smork of planet Terratow” to be recognized with exceptional accuracy. This keeps the experience of reading engaging, educational, and enjoyable.

Are you interested in natural language processing (NLP) and voice technology for kids? Check out our first “Lesson from Our Voice Engine” on NLP.

Don’t forget to give us your 👏 !

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Why Custom Language Models (CLMs) are Needed in Speech Recognition for Kids was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.