A primer on voice assistants and the technology behind them


It was early in 2015 and I was at my desk, which happened to be positioned close to the front door of my company’s office in San Francisco’s SoMA district.

A courier had just left a stack of Amazon boxes on a nearby table and people in the office started milling around, grabbing up their respective deliveries. As one particular coworker reached for a box with his name on it he looked over at me and said, “Alexa, what’s the weather today?”

“Huh?” I replied, confused as to why someone would ask me what it was like outside when we were sitting a mere 15 feet from floor to ceiling windows.

He chuckled and tapped the tape across the Amazon box, the strip of adhesive advertising the ‘Echo,’ Amazon’s latest foray into the hardware space.

“Amazon’s new voice assistant…she’s called Alexa. Pretty funny, right?”

Not the box in question, but similar — Photo Credit: The Krazy Coupon Lady

Oh yes. Hilarious.

I decided right then and there that I was never hopping on the voice train. 90% of the time ‘Siri’ didn’t know what I was talking about and now this new kid on the block had stolen my name, setting me up for endless ‘Alexa’ jokes that I would be forced to weakly smile at for all eternity.

No thank you, voice, no thank you.

Of course, the rest of the world wasn’t as salty about the introduction of Alexa as I was. The usability of voice has improved dramatically over the last four years and voice assistants are now the hottest new gadgets on the market.

According to Canalys, the number of worldwide smart speakers installed is set to grow 82.4% in 2019, surpassing 200 million units. To put that in perspective, 216.76 million iPhones were sold in 2017, and that was after 10 years on the market.

In addition, Grand View Research estimates that the global speech and voice recognition market size is estimated to reach USD 31.82 billion by 2025, fueled by rising applications in the banking, healthcare, and automobile sectors.

Voice is happening, and in case you too have been holding out on embracing the act of conversing with an inanimate object, let me catch you up to speed.

In this piece, we’re going to cover what voice technology is, how it works, who uses it, who is developing it, where it’s being used, and what we’re using it for. We’ll also take a look at what makes some consumers wary of adopting voice, like privacy concerns and apprehension around how voice assistant usage may lead to a lapse in common courtesy.

Hello, Computer

Though attempts at developing a verbally communicative relationship with machines have been taking place since the 1950s, it was only in the last 10 years that we got anywhere close to what Gene Roddenberry imagined when coming up with the voice-controlled computer utilized on the Starship Enterprise.

Voice Technology check-in, 1986 — Nope, still not there yet… (Star Trek IV: The Voyage Home)

Talking to inanimate objects used to be a behavior that would cause those around you be concerned for your mental health, however, these days controlling and interacting with your computer (or smartphone, speaker, watch, car, or microwave) through speech is fairly mainstream. Consumers to some extent have even come to expect a voice option, and take its availability as a feature into consideration when researching a purchase.

For instance, a recent survey of smart speaker owners performed by J.D. Power revealed that “59% of U.S. consumers said they were more likely to purchase a new car from a brand that supports their favored smart speaker voice assistant.”

That’s right, having Alexa onboard is right up there with heated seats and leather upholstery.

Beyond being a fun accessory or add-on, today’s voice tech services have many practical applications. Not to reveal myself as too much of a Trekkie (or Trekker?), but another piece of Starfleet technology affiliated with voice that has debuted in the real world is the ‘universal translator’.

Products on the market today such as Google’s Pixel Buds can translate 40 different languages in real-time, a feat that would’ve seemed impossible just a few years ago. Google announced last fall that the same functionality would now be available across all Google Assistant-enabled headphones and Android phones.

With voice turning from science fiction to just plain science, it does make one wonder exactly how the technology works.

Looking under the hood

Automatic Speech Recognition (ASR) is what makes this possible. It’s the process of turning human speech into something a computer can understand. The operation is much more complex than you might expect, so to keep it very high level, it goes something like this:

  • A person speaks into a microphone
  • The sound is processed into a digital format
  • The computer breaks the speech down into phones, bits of sound that correspond to letters –a cousin of the phoneme
  • Then the computer uses methods of pattern recognition and statistical models to predict what was said (Source)

This, of course, is just the most basic form of speech recognition, essentially providing the building blocks for activities like dictation or speaking your credit card number into an automated phone system. If you actually want to converse with a computer, the computer needs to not only hear the sounds you’re speaking but also understand them and their meaning — it needs context

Natural Language Processing (NLP), and its related subset, Natural Language Understanding (NLU), are a subfield of Artificial Intelligence (AI) that focuses on helping humans and computers converse naturally, while also comprehending the true meaning and intent of the speech.

If we can anthropomorphize a bit, computers are quite literal. Their human counterparts, on the other hand, tend to use language more figuratively. For instance when we tell a computer that we’re ‘killing it today,’ the computer likely thinks that someone or something is in mortal peril. (Source) Given the problems literal speech can cause, computers being taught the probability of a specific intent or context is imperative to a smooth voice experience.

Successful voice tech also hinges on the computer’s ability to learn and grow in its language abilities. This is accomplished through Machine Learning and its subset, Deep Learning, which use algorithms and statistics to analyze speech data to continuously improve computer performance of a specific task, which in this case is human conversation.

There’s a lot more to the puzzle of translating human speech to computers such as tackling the issues of audio quality, individual speech patterns, and accents, the last two being particularly important when creating a technology that will be used by a wide array of speakers.

Who uses voice technology?

The Spring 2018 Smart Audio Report from NPR and Edison showed that smart speaker ownership is evenly distributed across all adult generations, with women being a little more likely to take the smart speaker plunge than their male counterparts.

The Smart Audio Report by NPR and Edison Research

When it comes to those younger than 18, they like voice too. This year eMarkter expects “1.5 million kids — those ages 11 and younger — to use a smart speaker like Amazon Echo or Google Home, at least once a month. By 2020, that figure will grow to 2.2 million.” Children rely on voice assistants to play audio, tell bedtime stories, and even help them brush their teeth. Parents also like voice as a choice for children as it provides an alternative to screen-time, a concern that has been a hot topic in recent years.

When it comes to teen usage, eMarketer estimates that 3 million teens will use a smart speaker at least once a month in 2019. Teens aren’t heavy users of smart speakers due to increases in independence during the stage of life, however as avid smartphone users, teens are still likely to utilize voice tech on their mobile devices.

Who is developing voice technology?

All of technology’s biggest players are in the game, each with their own named, personified assistant.

As far as which is the best, that is up for debate. LoupVentures’ Annual Smart Speaker IQ Test compares the four main assistants (Google Assistant, Siri, Alexa, and Cortana) by asking them all the same 800 questions and seeing which performs the best.

Annual Smart Speaker IQ Test by Loup Ventures

In the most recent results, we learn that overall, Google Assistant is the strongest of the four assistants, but Siri is no slouch either.

You’d expect Alexa to be best at shopping, but the Amazon assistant answered only 52% of the commerce category questions correctly, compared to Google’s 86%. Cortana didn’t seem to be much competition at all, answering only 63.4% of the questions correctly and having its best showing as coming in third in the ‘information’ category.

Apart from accuracy, a survey of U.S. adults revealed that “How well [a voice assistant] understands me…” is the most important factor for users when forming voice assistant preferences. This means that in the end, you’re likely to adopt whatever technology understands you and provides the most seamless user experience.

Some named assistants coming out of Silicon Valley aren’t being marketed as end-user solutions themselves, but instead, are leveraged by other innovators to provide voice offerings that answer specific consumer needs. For instance, Audioburst relies on the power of IBM Watson’s NLU to understand the massive amounts of audio content we process each day.

Our CTO and Co-Founder, Gal Klein explaining how we use Watson to enhance the Audioburst experience

Of course, if Watson’s acute understanding of human language isn’t exciting enough for you, he also won Jeopardy! in 2011. So there’s that.

Why do we want to use voice tech?

That addition of ease in the navigation of daily tasks is likely the largest draw to voice technology.

Today’s society thrives on packing in as much into our days as humanly possible. We work, go to school, exercise, commute, cook, clean, socialize, shop, care for our loved ones, and maybe if we have enough time left over, we might also work in getting some sleep. In a world of constant multi-tasking and transitions from one context to the next, having our hands and eyes free can be a lifesaver.

The ability to utilize the benefits of technology through voice also aids accessibility. Lack of sight, dexterity, or literacy are no longer barriers to using and benefitting from computers and smart devices, leading to increases in independence and self-sufficiency.

Lastly, voice tech is just fun! Voice puts entertainment at the tip of our tongues, from trivia games to listening to streaming audio, to annoying our cats with smart speaker skills that are fluent in ‘meow’.

Where is voice technology currently used?



While the numbers here in the States are impressive, the rest of the world is catching up. Australia, while technically coming in with a lower amount of adults (5.7 million) using smart speakers, has a “user base relative to the population [that] now exceeds the U.S.” (Source)

Meanwhile, China is expected to see a 166% growth in the installed base for smart speakers going from 22.5 million units in 2018 to 59.9 million in 2019. (Source)

Now that we know where in the world voice technology is being embraced, it’s time to talk about the everyday locations where voice is popping up.

In Daily Life

According to the Voice Assistant Consumer Adoption Report, users have fully embraced the use of voice in the home with “over 40% of smart speaker owners now having multiple devices, up from 34% in 2018.”

This suggests that more and more users are finding it useful to have a voice assistant available regardless of where they are in the home at any given time.

The report also sheds light on which rooms are most likely to include a smart speaker. Use in the living room is the most popular by far (44.4% of users), but the bedroom (37.6% of users) and kitchen (32.7% of users) are also proving to be useful spots for voice interaction.

Outside of the home, it’s no surprise that with hands and eyes occupied, the car is one of the most popular spots in which to interact with voice tech.

“Nearly twice as many U.S. adults have used voice assistants in the car (114 million) as through a smart speaker (57.8 million). The car also claims far more monthly active voice users at 77 million compared to 45.7 million.” (Source)

Probably the most omnipotent location for voice is our phones.

Google’s ‘Voice Search’ and Apple’s ‘Siri’ debuted on our phones around a decade ago and were the first glimpses into what a voice-controlled world might look like. Mobile voice tech accuracy and usefulness have grown significantly through time and as of 2019, 70.2% of adults in the United States have given voice a try via their phones (Source).

Voice is with us wherever we go, which might lead one to wonder: What exactly are we doing with it?

Voice tech applications


In an article for Machine Design, use cases were laid out for voice tech in the medical field. For example, during an exam, “having a listening device in the room with [a] patient has a lot of potential for capturing clinical notes, identifying billing codes, or even providing clinical decision support during the encounter,” freeing up the doctor to focus not on paperwork, but on the person whom they’re treating.

Another space where voice is getting interesting is Customer Service.

Most people can relate to the frustration of having a poor call with a customer service department, or even worse, their automated voice system.

However, with the advent of emotion recognition software, friction-filled support calls may be a thing of the past — it can “recognize customer emotion by considering parameters such as the number of pauses in the operator’s speech, the change in voice volume, and the total conversation time in order to do a real-time calculation [of] a Customer Satisfaction Index.” (Source)

There are many different ways emotion recognition technology could be implemented in a real-time support interaction.

For instance, knowing whether a customer is upset might allow a voice system to switch their approach with the customer, or perhaps transfer them to a human representative when the computer ‘senses’ that a call may be going south.

Customer Support solutions aren’t the only application of emotion recognition either.

For instance, we use it here at Audioburst to help determine the context and intent of new audio when it is imported into our system. Knowing whether a specific piece of content is happy, sad, angry, anxious, or even just neutral plays a vital role in providing personalized listening experiences, tailored to our users’ environment, interests, and personalities.

How consumers are using voice assistants


  1. Search covers queries like asking a general question, checking the weather, news, or a sports team’s current standings. These queries require the voice assistant to understand the true intent and context of the question, and then externally seek and return the correct answer.
  2. Commands are much more straightforward, including tasks like setting an alarm, making a phone call, or streaming audio from a chosen app.

The top three uses of smart speakers are asking general questions, streaming music, and checking the weather, with over 80% of smart speaker owners having tried these functionalities at least once. The above report notes one interesting piece of data from the use case results: smart home control is ninth in terms of whether or not a user has ‘ever tried’ the feature but fourth for daily active use.

Read: while not everyone has smart home devices such as lights or thermostats, those who do are likely to use their smart speaker to control them every day.

In-Car, voice assistants are used to take care of tasks like making a phone call, texting, asking for directions, and queueing up audio entertainment selections. These tasks would otherwise require the driver to pull over or take their attention away from the act of driving.

With many municipalities invoking ‘hands-free’ laws for drivers, the functionality is not only convenient but imperative.

Beyond using smart speakers at home and embracing in-car assistants, voice technology can also be found scattered throughout daily life. Taking orders at restaurants and even providing concierge services at hotels. New uses are emerging every day and it’ll be interesting to see where voice will install itself next.

Despite this rapid adoption, there is still some hesitancy

There are reports of personal conversations being unintentionally sent to random people in a user’s contact list, Alexa maintaining a record of every conversation you’ve ever had with the device (you can delete it), incidents of Alexa spontaneously laughing (not a privacy risk, but definitely creepy!), and the recent revelation that Amazon employees are actively listening to user conversations.

However, as alarming as these examples may sound, privacy concerns don’t seem to be stopping people from buying smart speakers.

Voicebot points out that though ⅔ of U.S. consumers have some amount of concern over privacy issues with smart speakers, it doesn’t necessarily appear to be a barrier to purchase and adoption.

“The privacy concerns for all consumers and those that do not own smart speakers are nearly identical. For example, only 27.7% of consumers without smart speakers said they were very concerned about privacy issues compared to 21.9% of device owners. This means that even some consumers with privacy concerns went ahead and purchased smart speakers.”

There are also concerns that barking orders at smart assistants all day may be making us forget our manners.

While the concern is for both adults and children, when it comes to kids, tech companies themselves are putting some behavior modification solutions into play in the form of ‘please and thank you’ apps and skills. There are even camps that are vehemently opposed to showing artificial intelligence the same courtesies we show fellow human beings.



Voice is changing how we interact with the world.

The technology is improving at record speeds and all eyes are on the space. It’s exciting to think about how additional research and data, as well as advances in technology and understanding, will influence voice communication’s ability to grow and evolve.

As for me, I’ve been the subject of approximately 4,782 Alexa jokes since that initial jab in 2015. While I know they are intended to be funny, I still can’t suppress my instinct to sigh and roll my eyes, reminiscing about the good old days when no one had ever heard of the name Alexa.

That being said, as I sit here at my desk, preparing to go to bed, I’ve found myself lifting my phone to quietly ask Siri to set my alarm for 7 am and to turn off the lights.

I must’ve gotten on that voice train after all.


Artificial Intelligence (AI) is everywhere these days. From chatbots to autonomous cars to our very own search platform, computers are working hard to help improve everyday life. But how do they do it, exactly?

We thought it’d be fun to give you a short primer on how AI aides Audioburst in our mission to organize the world’s audio content.



In order to provide you with the best search results possible, our engineers have come up with a set of algorithms.

An algorithm is basically a set of rules used to resolve a problem….kind of like learning PEMDAS back in your high school Algebra class. A mathematical algorithm, like the order of operations, gives you instruction on how to solve a math problem. Quite similarly, a programming algorithm is a set of problem-solving instructions given to a computer to assist in attaining a desired result in a computer application.

In the case of Audioburst, that means that we have developed a set of algorithms based in two branches of AI, Natural Language Processing (NLP) and Machine Learning, which take different factors (trending stories, topics of interest, listening habits, intent, etc) into consideration when deciding what audio ‘bursts’ we provide when you query Audioburst Search or News Feed, our Google Assistant / Alexa skill.  

Natural Language Processing


In order for the system to be able to produce search results, it needs to understand the meaning of the search terms, but even more importantly, the content of all of the possible results. This is where the use of Natural Language Processing (NLP) technology comes into play. NLP is a type of artificial intelligence that facilitates communication between people and computers using human language. A subset of NLP is Natural Language Understanding (NLU). NLU dials in on the comprehension aspects of natural language communication. It’s important because it isn’t enough to just have a basic vocabulary with the ability to complete simple conversations. You also need the ability to determine the intent of the language if you are going to successfully communicate without excessive mistakes.  

By harnessing the power of NLP and NLU, Audioburst is able to listen to, understand, segment and index millions of minutes of daily talk content from thousands of top audio sources including radio, podcasts, and TV in real time. This thorough analysis is part of what makes Audioburst so special. We don’t just take your request for audio based on a certain topic, event, or keyword and match it up with news headlines trending on text-based search engines. Instead, this deep understanding of both content and user need aids our platform in providing the right story, at right time, from the right sources.

Machine Learning


Machine Learning is AI that allows a computer to analyze data and use statistics in order to improve its ability to perform a specific task, or “learn” without being directly aided by programmers.

Audioburst’s platform is constantly learning. Using the above mentioned NLP and NLU technology we already have a deep understanding of what is happening in the news. However simply knowing what’s in the news isn’t enough to provide the best results. Just like with real human interaction, you also need to consider context, intent, and tone in order to know exactly what a listener is looking for in a response.

For example, let’s take a look at the ambiguous potential of the search term ‘Kim.’ It’s included in both stories about the infamous North Korean leader, Kim Jong-un, but it can also found just as plentifully in stories about reality TV star, Kim Kardashian. Our AI is extremely versed in both world news and politics, as well as entertainment and juicy celebrity gossip. When audio content about either of the ‘Kims’ is received, the platform is able to categorize them into their appropriate categories. That in itself is extremely helpful, but it gets better: even in a week where President Trump has both Kims appearing in his news coverage, Audioburst can still track and associate each story with its appropriate context.

That is just one example.

Machine learning is also the technology that helps us identify new stories. In this case, we’re going to focus on the search term ‘Michael.’ Most of the time, a user searching for information about Michael is going to be looking for information on a famous person, such as Michael Jackson, or Michael Jordan. However, last month when a powerful hurricane formed in the Atlantic, the next name on the World Meteorological Organization’s Tropical Cyclone Names list for the region happened to also be ‘Michael.’ Within moments of Hurricane Michael news hitting the airwaves and being indexed by Audioburst, a query to our platform for “Any news about Michael?” suddenly had a completely different meaning. Through the power of machine learning, our AI made sure that users seeking pertinent information about the powerful storm were hearing the most up to date information about the correct Michael at a time when accessing that news was critical.

As you can see, our AI is an extremely powerful tool that helps drown out the noise, surfacing only the most relevant information. With each search interaction, the platform learns more about the user, and their preferences, interests, and habits teach the system how to provide more accurate and meaningful results. When you combine this strong understanding of the individual with the ability to process audio in real-time,  you create the experience that has made Audioburst untouchable in the realm of audio search.


The #AskNewsFeed Challenge


We hope you enjoyed this glimpse into how AI is powering the next generation of audio here at Audioburst. We also wanted to take a moment to let you know about a fun event we are currently running.

The #AskNewsFeed Challenge is a contest that helps us challenge and stretch the boundaries of our AI by inviting you to do your best to stump our Google Assistant / Alexa skill, News Feed.

The contest is on now, however you can still register here, with full details on our blog. We feel pretty confident in our AI’s abilities, so hit us with your best shot!