Decades ago, talking to a computer was only possible in advanced scientific labs or in science fiction stories. Today, voice assistants have become a reality of everyday life. People talk to their phone, smart speaker, doorbell, and even microwave oven. Voice is gradually becoming one of the main ways to interact with consumer applications and devices and the use of our natural language as a mode of interaction is extremely appealing. Software like text to speech (TTS), automatic speech recognition (ASR), and Spoken Language Understanding (SLU) are used to recognize and process human language.

But while we’ve seen a lot of progress in the application of voice interfaces like google assistant or Siri in consumer applications, the business sector still lags behind, even though enterprises can be the main beneficiaries of advances in speech recognition and overall interactive voice technology. Where workers are engaged in hands-on activities and can’t interact with graphical user interfaces, voice user interfaces can make a huge difference in user engagement, productivity, and safety. However, the enterprise voice sector must overcome several challenges, one of them being privacy and security concerns. Today’s consumer voice assistants are not renowned for being very privacy friendly. There have been several documented incidents of smart speakers and voice assistants mistakenly recording conversations and replaying them elsewhere. And the massive user data that these assistants collect gets sucked into the black hole of the data-hungry tech giants that run them.

The expansion of the voice interface to your living room, car, office, pocket, and wrist has created fierce competition between tech giants. Manufacturers of smartphones, smart speakers, wearable devices and other mobile devices aim to create the ultimate voice experience that can respond to every possible query, whether it’s asking the weather, turning on the lights, responding to emails, or setting timers. Currently, the only way speech api vendors can get ahead of competitors is to improve their AI models by expanding their repertoire of actionable voice commands. This puts them in a position to have a vested interest to collect more user data and assemble larger training datasets for their AI models.

What’s also worth noting is that all major consumer voice assistants are owned by companies that  have built their business on collecting user information and creating digital profiles to serve ads, provide content and product recommendations, and keep users locked in their apps. In this regard, voice interfaces become another window for these companies to collect more data and know more about their users.

This brings us to an important takeaway: Tech giants will do anything they can to own your data because that is their key differentiating factor.

From a security and privacy standpoint, this causes several key concerns:

– These intermediaries will get to hear private conversations of enterprises’ users. For instance, if you allow a consumer voice assistant to check on your bank balance, you’re giving them access to this sensitive information.

– You don’t know what kind of data is being collected and where it is stored.

– Data is stored centrally in the servers of the voice AI provider. And as numerous security incidents have shown, centralized stores of data are attractive targets for malicious actors.

– As an enterprise, you have no ownership or control of your data and can’t use it to improve your products or gain insights about how users interact with your applications.

– In case you’re handling sensitive health, financial, or business data, you’re at the mercy of the Voice AI vendor to keep your data safe and not share it with third parties.

On the other hand, the Alan Platform is designed to ensure security and privacy for users of the enterprises and organizations. The key privacy tenet of the Alan platform is that each enterprise is the sole owner of their user conversations data. They decide where it is stored and who has access to it. And regardless of a customer’s choice for where to store their data, Alan AI secures this data, making sure it’s encrypted in transit and at rest. Not only does this model create more value for businesses in comparison to the classic voice AI platform, but it also addresses the key privacy and security pain points that organizations face when considering voice interfaces for their applications.

The Alan platform is based on solving specific problems for each enterprise, not answering every possible query in the world. Each deployment of our AI system will be tuned for one or more applications of a single enterprise.

The value of the Alan Platform does not come from creating digital profiles and selling ads and products to users, therefore there’s no incentive to collect, hoard, and monetize user data. Instead, Alan AI seeks success by creating value and helping businesses reduce costs, improve operational efficiencies and safety with employee facing deployments, and increase revenue acceleration for the customer facing deployments.

The goal is to increase ROI for businesses by deploying voice interfaces for apps being used by their customers and employees. This is why Alan AI believes every company should have full control and ownership of their data and AI models to provide the required privacy for their users. An added benefit is that the AI of each customer will improve as it continues to interact with the users of its application, and the business will have a chance to glean actionable insights from its data and develop new features and products.

Having access to the right quality and amount of data can give an enterprise the edge in providing a higher quality voice interface. Therefore, every enterprise should put data ownership and security at the center of its product innovation strategy. Will you prefer to use the technology of a company that works behind a black box, taking control and ownership of your data and not providing clear safeguards, or do you prefer to be in control of your data and work in a secure environment where you can continuously innovate and improve the voice interface of your products? If you’re in the latter camp,  the Alan Platform is for you. At Alan, we believe the future is a human voice interface to app. 

Reach out to sales@alan.app to set up a free private demo of the platform or answer any questions that you may have about the technology.

Intelligent voice interfaces for apps have become ubiquitous. From making calls to purchases, the use cases are explosive. Its use in educational institutions as a learning aid is yet to reach its full potential, but we are certain it is on the right track and can revolutionize the way students are educated. Given the hybrid learning trend, remote learning intertwined with the physical classroom, the challenge is to keep the student engaged and learning, regardless of the environment they are in.

To achieve critical education outcomes, it is important to focus on both technology and 21st century skills. Voice-based learning is an aid that includes a broad range of tools and enables a blended learning model- augmenting the learner’s experience and help educators with their teaching methodologies.

Voice tech applications are getting smarter over time with advances in artificial intelligence and their application in voice technology. Instructors  can simply ask their app “How many students submitted their homework assignment?”, “Who was absent in class today?”, “What are the instructions for today’s science fair?”, “ Summarize the progress of student Andy Jacobs” etc. Voice interfaces enable applications to give the right answer, faster.

Let us look at what makes voice technology a terrific aid in classrooms:

1. Collecting data in real-time:

Voice enabled devices are great at collecting data in real-time. Using them, teachers can record students’ engagement in class, monitor participation, attendance, etc. This is a productivity tool for teachers as they can just speak to the app instead of tedious touch and type. Moreover, built in artificial intelligence and analytics capabilities empower the instructor with data analysis and real-time insights. This empowers the instructor to quickly tackle situations that need a bias for action. 

2. Academic tracking and feedback:

The academic progress of students can be tracked over a period of time using voice interfaces. It can be done at scale for every student in the institution. It can also remind students about what is expected of them regarding assignments, deadlines, subjects they have enrolled in, etc. The institution can also use voice interfaces to deliver personalized feedback and constant updates on what is happening in the classrooms. Timely feedback on student performance is an important mechanism for management of academic outcomes- voice tech can definitely be used to accomplish this.

3. Communal learning:

When using voice interfaces, everyone in the classroom hears the same information uniformly without any bias. The students can maintain eye contact without looking down at the computer screen. The teachers also don’t have to break eye contact with the students, thereby helping build a closer rapport with the students.  

4. Accessing records:

Accessing student record details quickly is often difficult, even if you use a student information system. Voice interfaces make this an easy process as they are adept at large data sets. For example, if a teacher wants targeted information about a student, all they need to do is ask the app. It will share the information as soon as the question is asked. It is not just limited to academic records as educational institutions can get their entire data that was input into the system.

5. Personalizing learning:

Thanks to the human-like features of a voice interface, it makes learning more personal and humane for the students. Students will find it easy to follow instructions from voice interfaces because of their ability to express a wide range of emotions and voice modulations. Also, personalization means accommodating different learning styles of a student body and making some adjustments to fit their unique needs.

6. Introducing routine learning exercises:

Institutions can use voice assistants to introduce routine learning exercises such as learning words, memorizing spellings and facts, learning common phrases from foreign languages, etc. The use of voice as an aid for this is definitely a time saver for the teacher. Such methods can also positively drive engagement of students, as the voice can be blended with music to make it more appealing.

7. Customizing tests:

Voice technology can be customized according to the needs of the student. It can come with a bunch of ready-made templates that the teacher can choose from, on a whim. Moreover, a teacher can use different templates to match the diverse student personas in a classroom.

8. Storytelling:

We all love stories. Voice interfaces can be used to read stories to students. It could be specific to the subjects that are being taught or for the pure joy of listening to a story. It keeps the students engaged, but it also gives an opportunity for the teachers to rest. Interactive stories with engaging plot lines as a mode of instruction can help the student perform much better in classrooms. 

9. Controlling the environment:

Teachers can use voice interfaces to control the classroom by setting the tone with instructions. These can be repeated and also modified rapidly to inform students in the classroom on protocols for learning sessions, tests, and any special announcements.

In summary, Voice interfaces can be used to deliver an immersive learning experience and make learning more attractive to both student and instructor. They are a useful aid to the institution to deliver the right education at the right time to the right student.

The team at Alan AI will be more than happy to assist you with any questions or provide a personalized demo of our intelligent voice interface  platform. Just email us at sales@alan.app

About Alan AI:

Alan’s voice interface leverages the user context and existing UI of applications, a key to understanding responses for next-gen human voice conversations. Alan AI has patent protections for its unique contextual Spoken Language Understanding (SLU) technology to accurately recognize and understand human voice, within a given context. Alan’s SLU transcoder leverages the context to convert voice directly to meaning by using raw input from speech recognition services, imparting the accuracy required for mission-critical enterprise deployments and enabling human-like conversations, rather than robotic ones. Voice based interactions, coupled with the ability to allow users to verify the entered details without having the system to reiterate inputs, provides an unmatched end-user experience.