There are numerous API providers in the chatbot landscape, the majority of them are focusing on Natural Language Processing (NLP) and Natural Language Understanding (NLU). It is the crucial step to decide since it will be handling the most important step in a conversational interface.
What is the difference between NLP and NLU?
- Natural Language Processing (NLP): In the artificial intelligence (AI) context, NLP is the overarching umbrella that encompasses several disciplines that tackle the interaction between computer systems and human natural languages. From that perspective, NLP includes several sub-disciplines such as discourse analysis, relationship extraction, natural language understanding and a few others language analysis areas (see Figure 2).
- Natural Language Understanding (NLU): NLU is a subset of NLP that focuses on reading comprehension and semantic analysis. The combination of NLP and NLU technologies is becoming increasingly relevant on different software areas today including bot technologies. While there are many vendors and platforms focused on NLP-NLU technologies, the following technologies are becoming extremely popular within the bot developer community.
Figure 2: How NLP and NLU different.
To learn more about the differences between NLU and NLP you can read our NLU vs NLP: Main Differences & Use Cases Comparison article.
Top 5 NLP platforms
Dialog Flow (ex API.ai) has capabilities to build speech to text and text to speech, powered by machine learning. It provides built-support for currencies and date. Supports majority of the platforms like Facebook Messenger, Slack, Alexa, and Google Assistant. It supports multiple devices ranging from laptop computers to cars. Currently supports 20+ languages. It’s free for a limited number of queries.
Wit.ai is a free platform including for the commercial use. There are no limits on request number except they ask you to notify if you are going to exceed 1 request/sec. Supports many languages. On the other side, when your app is open, your intents, entities and validated expressions will be accessible to the community but not your logs, but still, you have the ownership of the data. Used by more than 120,000 developers. Supports not only chatbots but also wearables and home devices too.
Luis is Microsoft’s platform. It stands for Language Understanding (LUIS). A machine learning-based service to build natural language into apps, bots, and IoT devices. Quickly create enterprise-ready, custom models that continuously improve. It supports many services, but they have nice features for Azure integration.
4. Amazon Lex
Amazon Lex is an AWS service for building conversational interfaces into applications using voice and text. With Amazon Lex, the same deep learning engine that powers Amazon Alexa is now available to any developer, enabling you to build sophisticated, natural language chatbots into your new and existing applications. Amazon Lex provides the deep functionality and flexibility of natural language understanding (NLU) and automatic speech recognition (ASR) to enable you to build highly engaging user experiences with lifelike, conversational interactions and create new categories of products.
5. Watson Assistant
Watson Assistant, formerly Watson Conversation, helps you build an AI assistant for a variety of channels, including mobile devices, messaging platforms, and even robots. Create an application that understands natural-language and responds to customers in human-like conversation –in multiple languages. Seamlessly connect to messaging channels, web environments and social networks to make scaling easy. Easily configure a workspace and develop your application to suit your needs.
See our article about IBM Watson for more details.
Natural Language Platforms (NLP) Comparison
Below table is the comparison of these five NLP platforms based on their features.
|Allow Import/Export Model
|Recognize User Intent
|More than Basic Parameters
|Pre-built Intents (Domain of Knowledge)
|Around 35 Domains
|Around 170 intents
|Save Progress through Session
|Yes, through Google Speech
|Yes, through Bing Speech
|Yes, through IBM Speech to Text
|Limits for API calls
10k text queries
5k speech queries
FREE: 10k queries/month 5 queries/second PAID: 10 queries/second $0.75 per 1k queries
Free: 1k API queries/month PAID: Unlimited API queries/month Up to 20 work spaces Up to 2k intents Premium: Unlimited
TRIAL: 1 year PAID: $0.004 per speech query $0.00075 per text query
10k API queries/month
$0.75 per 1k querries
FREE: 1k API queries/month STANDARD: $0.0025 per API call PREMIUM: Available Upon Request
|Simple B2C chatbots, MVPs
|Middle Level B2C chatbots, virtual assistants, MVPs
|Preview Mode, too early to judge
|Cortana functionality, IoT applications, Virtual Assistants, and Chatbots
|Virtual Assistants and chatbots that require IBM integration
Courtesy of (Digiteum)
If you still feel like you need NLP platform selection guide, feel free to check our related article.
To learn more regarding the future of NLP you can read our Top 5 Expectations Regarding the Future of NLP article.
And if you have a specific business challenge,
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
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Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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