NLU vs Strict Commands: spot the differences!

Automatic Speech Recognition (ASR) technology has transformed the way humans interact with machines, revolutionizing the artificial intelligence (AI) market by adding greater nuance and depth to human-machine interaction. By integrating Natural Language Processing (NLP) and Natural Language Understanding (NLU), ASR has enabled systems to analyze human speech, interpret the meaning, and generate accurate responses. These technologies offer a more intuitive and natural approach to interactions, making it easier for users to communicate effectively with the systems they use, offering near real-time responses.

Over the years, Vivoka has developed two main forms of voice control: Grammar-based Automatic Speech Recognition, which uses strict commands, and Intent-based commands, powered by NLU. Both forms have different advantages depending on the industry, type of tasks, and operational environment in which they are used. Each form leverages models designed to interpret and analyze speech patterns, enabling more accurate learning from user inputs.

Before selecting one of these voice control Technologies for your business, it’s essential to fully understand their differences and identify which technology will best suit your company’s needs.

What is ASR Grammar-Based (Strict Commands voice AI)?

man in a warehouse talking to a voice controlled device

Strict commands Voice AI relies on a set of predefined commands that the system is programmed to recognize. This means that the device will only respond to these predefined sentences or phrases and will not be able to interpret variations in phrasing and won’t understand the user’s intents. If a user gives a command that is not included in the system’s list, it remains unable to perform the task.

Although strict commands might seem limited because the device can only react to specific phrases, Grammar-based ASR offers many advantages and remains versatile in specific contexts:

  • High accuracy: Since the system’s model recognizes a limited range of predefined sentences, the likelihood of errors is greatly reduced. This is especially beneficial in precision-driven environments. For instance, in logistics, tasks like verifying stock levels can be streamlined by using simple, predefined commands like “check,” “next,” or “confirm.” These tasks do not require extensive conversational capabilities, making strict-command ASR an obvious fit.

     

  • Fast and reliable: With fewer variables to handle, ASR with strict commands delivers quick and reliable responses to user input, reducing wait times. Since the commands are predefined in the system, it won’t take long for the device to handle the tasks given by the user. This predefined command structure allows the system to execute tasks more efficiently, without needing to analyze or interpret varied phrasing. This makes it especially useful in high-paced environments, where both speed and accuracy are essential, as the system can instantly recognize and act on familiar commands without any delays caused by complex processing.

     

  • Cost-efficient: Grammar-based ASR typically requires less complex data processing and fewer resources than models relying on NLU, which depend on additional machine learning models to process natural language data. As a result, strict commands can be more economical for businesses that don’t need complex conversational capabilities.

     

The use of Grammar-Based ASR in specific industries

Man holding a cupboard box in a warehouse

Voice technologies like Automatic Speech Recognition can significantly enhance efficiency in sectors where precision and quick response are paramount. By employing strict-command ASR, various industries can optimize their workflows, minimize errors, and improve task execution. Here’s how ASR technology is making a difference in specific fields:

Warehousing and Logistics: In these sectors, workers often perform repetitive tasks such as order picking or inventory management. In these scenarios, strict-command ASR is highly effective. With a simple set of commands, workers can streamline tasks, reduce errors, and increase overall productivity.

 

Field Services: Technicians in field services who carry out repetitive actions such as diagnostics, system checks, or maintenance should benefit from ASR with strict commands. Predefined commands like “start scan” or “reboot” ensure precision and efficiency without the need for more complex interactions. These predefined models offer quick response times, allowing technicians to complete tasks faster and more efficiently.

Healthcare: In healthcare settings, strict-command technologies offer simplicity and precision for controlling medical devices during routine procedures. With a limited number of predefined commands, accuracy is ensured, and the risk of misinterpretation is reduced.

What is Natural Language Understanding (NLU – Intent-Based Commands)?


To begin with, NLU is a subfield of Natural Language Processing (NLP) that focuses on comprehending human language. Unlike Grammar-based Automatic Speech Recognition, which relies on rigid commands, ASR combined with NLU aims to understand the intentions behind user input. It does not rely on predefined commands, but instead utilizes NLU, a key component of conversational AI technologies, to interpret user speech based on sentence meaning and conversational context.


NLU has wide-ranging applications across various industries. For businesses, it offers solutions for speech data analysis, conversational AI, and voice-enabled equipment and devices. The company Vivoka provides cutting-edge NLU technology that can be employed by customers to enhance their business operations. 

By enabling a more conversational interaction, NLU-based Commands (NLU technology) offers several advantages:

  • Flexibility: Workers no longer need to remember exact phrases or commands. With NLU-based systems, they can speak more freely, using their own words to issue commands. By understanding the intention behind unpredefined words, the system and the worker can interact naturally together.

     

  • Enhanced user experience: Because users can speak in a more natural manner without having to mind their utterance, NLU provides a more intuitive and user-friendly experience. Workers are less burdened by remembering specific commands, and the system can adapt to a wide range of input styles. This is especially useful in industries with diverse workforces or where different language abilities are present.

     

  • Advantage in Multilingual Environments: this solution is especially beneficial in multilingual environments, where users may encounter cognitive challenges when required to follow strict voice commands. By providing more flexible voice interactions, it reduces the strain on users who might not be fluent in a single language, thus improving overall user experience and efficiency.

     

  • Contextual understanding and sentiment analysis: NLU systems don’t just process words, they create the impression that the user is not merely issuing commands to a machine, but rather engaging in a conversation with an AI-powered device capable of understanding the meaning behind what is being said. By processing both the user’s intent and the sentiment of their input, these systems make the interaction feel more like a natural dialogue, rather than a set of rigid commands. This fosters a more intuitive and engaging experience, as the user feels the system is not just responding to words but comprehending the deeper context of the conversation.

  • Less onboarding & training time: Natural Language Understanding (NLU) reduces onboarding and training time by eliminating the need for users to memorize predefined commands, allowing for intuitive and flexible interactions with the system. Users can speak in their natural language, making the system accessible and easy to use right from the start.

 

The use of NLU-Based in specific industries

  • Warehousing and Logistics: In fast-paced environments like warehouses, where instructions may vary depending on the situation, Intent based commands provide the flexibility workers need to stay efficient. For instance, a worker can say “move this to section B” or “transfer this to B”, and the system will interpret the intent behind the command, reducing errors and improving productivity.

     

  • Field Services: In field services, Intent based commands are highly beneficial in situations that demand multitasking or troubleshooting. Workers can issue commands conversationally without worrying about precise phrasing. For example, a technician may issue commands like “run a diagnostic” or “check the system” in varying forms, and the system will still interpret and manage these instructions correctly.

     

  • Healthcare: During surgical procedures or other high-pressure applications, medical staff may not have the mental bandwidth to recall specific commands. With Intent based commands, they can communicate naturally, allowing them to focus on the task at hand. However, it is recommended to implement strict commands for voice-controlled medical devices that directly impact patient health, to ensure that the commands are accurately understood and executed by the machine.

Which voice control technology suits your business needs better? ASR, or Intent based commands?

Both Grammar-based ASR and NLU-Intent Based commands share a common goal—improving human-machine interaction—both Automatic Speech Recognition and NLU technologies are employed across various industries.

Un médecin dans un bloc opératoire qui manipule un outil par contrôle vocal.

On one hand, Grammar-based ASR excels in environments where commands are structured and precise. For businesses where accuracy and predefined instructions are critical, strict-command Voice AI ensures fast and reliable execution. With the help of machine learning models, businesses can enhance their customer experience by leveraging speech recognition, voice solutions, and AWS solutions for better conversational interactions.

On the other hand, NLU provides more flexibility and adaptability, allowing users to issue commands in a more conversational style. NLU, a conversational AI solution, shines in dynamic environments where task complexity and workforce diversity require systems that can interpret commands based on intent and context. By using NLU, businesses can cut down on the repetitive manual work and rely on robotics and machine learning models for language understanding and natural language processing.

While both technologies can be used in the same industries, the best choice for your business depends on the nature of the tasks, the level of complexity, the applications, and how flexible your workflow needs to be. Whether you require the strict command structure of Grammar-based Speech recognition or the conversational capabilities of NLU, both technologies offer significant advantages for improving productivity, solving cutting-edge problems, and enhancing the customer experience.

Our fully embedded solutions set us apart by offering these sophisticated technologies in a non-cloud, self-contained format, enhancing security and performance without dependency on internet connectivity. This approach allows teams to leverage advanced data modeling and voice recognition capabilities directly on their devices, ensuring faster response times and greater reliability. By adopting our embedded systems, businesses can develop robust, efficient voice control solutions that enhance operational efficiencies and foster superior customer experiences. Whether you require the meticulous accuracy of Grammar-based Speech recognition or the conversational flexibility of NLU, our technology provides the crucial advantage of high performance and enhanced security, crucial for pushing the boundaries of what’s possible in human-machine interaction.

Our solutions are specifically designed to prioritize privacy and performance by using fully embedded systems that operate independently from cloud services. This means that all data remains on the device, avoiding storage in the cloud, which significantly enhances the security and privacy of sensitive information. By leveraging advanced techniques in voice recognition and data modeling, we apply science at the core of our products to solve real-world problems efficiently and securely.

Our approach is deeply rooted in a culture of experimentation, allowing us to explore large-scale applications and continuously refine our offerings. This commitment to applied science and innovative techniques ensures that our solutions are not only private but also robustly designed to enhance operational efficiencies and customer experiences. With our technology, businesses can solve complex challenges through powerful, secure, and private voice control systems, pushing the boundaries of what’s possible in human-machine interaction.

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