What is ASR technology and what are its advantages for the contact center?

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<h3>Learn what is ASR technology, how it enhances the customer experience, and how contact centers can implement and improve it in a cost-effective way.</h3>
Alexa, when will the world end? This may sound like a silly question, but one that many people place to their phones. In spite of all of the technological advances, not even AI-empowered virtual assistants are capable of predicting the future;  however, they can understand, interpret, and answer a lot of other questions.
Behind Alexa, Siri, and other virtual assistants there’s a technology first created in the 50s and improved throughout the years. If you use virtual assistants in your day-to-day life (to schedule meetings, call people, or do grocery shopping), you already know how they can simplify most mundane tasks. But have you considered how ASR can improve the customer experience (CX) in the contact center?
 
In this blog, we take a closer look at:
<ul>
<li>What is ASR.</li>
<li>ASR evolution through the years.</li>
<li>How can contact centers benefit from ASR.</li>
<li>How to continuously improve ASR systems.</li>
<li>What is ASR technology?</li>
</ul>
 
ASR stands for automated speech recognition—a technology that allows computers to hear from humans and convert speech into text. It can be used for data entry, quality control, or a human-like conversation. Primarily used to provide information and forward calls, contact centers can also benefit from ASR to improve both the customer and agent experience.
ASR is a subfield of artificial intelligence (AI), also referred to as “speech-to-text” or “speech recognition”.
 
 
<h4>ASR through the years: from recognizing digits to personal assistants.</h4>
ASR came a long way from its first form to today’s interactions with voice assistants. Although you don’t need to fully understand it to benefit from ASR, it’s interesting to see its evolution throughout the years:
1952. The first automatic digit-recognition machine was created. It would recognize digits zero to nine with an accuracy of more than 90% when spoken by its creator and around 70% with other speakers.
1962. <a href="https://www.youtube.com/watch?v=rQco1sa9AwU" target="_blank" rel="noopener">IBM debuts a machine</a> able to understand digits zero through nine and words like “minus, plus, subtotal, false, and off. By the end of the decade, researchers in the Soviet Union developed an algorithm able to recognize about 200 words.
1971. ASR technology would prove to be valuable for many areas of the military and national defense. The US Department of Defense funded the Speech Understanding Research (SUR) program. Later scientists from Carnegie Mellon University created a speech recognition machine that understood 1011 words and translated complete sentences.
1980s. A decade later, the first voice-activated typewriter was created. It had a vocabulary of 20000 words. Unlike the first iterations of voice-commanded machines, it was developed with a data-driven approach to predict speech patterns instead of rule-based.
1997. A revolutionary continuous dictation software is released, able to recognize 100 words per minute and paving the way for speech-to-text use cases.
2008. Computers can be taught to understand the different variations of human speech, including accents, pronunciation, and context. Google Search by Voice was launched and helped companies implement personalized speech recognition on smartphones.
2011. Apple launched voice assistant Siri. Apple’s virtual assistant can translate, check email, send text MessagePad, schedule calls, get sports information, check the weather, and perform many other common day-to-day tasks.
2014. Microsoft unveils Cortana, the company’s AI-powered personal assistant.
So, while it debuted in the 50s, it was only in the XXI century that ASR became widely available commercially. It can now be found in many products of our daily lives.

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Following the launch of Siri in 2011, voice assistants took off as a new paradigm of interaction. They have gained a second wave of momentum with their introduction to AI-powered chatbots and smart speakers. What does the future hold for voice assistants?

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Let&#8217;s deep dive into what ARS means for a contact center and use-cases for improving customer service.
<h4></h4>
<h4>How can contact centers use ASR technology?</h4>
Most CX professionals recognize the value of AI to increase operational efficiency and deliver better customer service. In fact, McKinsey found out that <a href="https://www.mckinsey.com/business-functions/operations/our-insights/how-advanced-analytics-can-help-contact-centers-put-the-customer-first" target="_blank" rel="noopener">companies are leveraging advanced technology</a> to reduce the average handle time up to 40%, increase self-service containment rates up to 20%, and cut employee costs by up to $5 million.
In contact centers, ASR is used on interactive voice response (IVR) systems, eliminating, for example, the need to press a certain key during a call to get to the most appropriate agent.
Contact centers have been using ASR technology for decades but often fail in delighting customers. Most of the time, IVRs feel like a series of endless options and repetitive steps that don&#8217;t contribute to the resolution of the issue. Even most chatbots are limited and can’t interact with customers in a conversational manner.

With conversational AI, contact centers can use advanced speech technology with deeper intelligence and automation.

The use of conversational AI in contact centers will be game-changing

AI is revolutionizing speech recognition technology and introducing new systems and tools into contact centers with built-in conversational AI. These tools can neatly replace the traditional IVRs—giving end-customers a piece of technology that provides them with a pleasant experience.
By leveraging ASR technology to implement smart conversations with customers through voice assistants and chatbots, contact centers enhance the customer <a href="https://www.talkdesk.com/cloud-contact-center/self-service-experience/" target="_blank" rel="noopener">self-service experience</a> while freeing agents to focus on more complex requests.

Customer service chatbots can both improve customer service while simultaneously easing the burden on human agents.

How chatbots are changing—and improving—customer service

ASR technology can be used in contact centers to free agents from repetitive, low-value tasks or improve CX.
Below, you can find some ARS use cases for the contact center.
Call transcription.
Call transcription occurs when the system automatically translates phone or video calls into text and stores them in your database or platform. It can be either in real-time or based on past call recordings. Call transcription can be used in the contact center to automate after-call work, collecting and updating databases and systems with customers’ information.
Conflict resolution.
Handling angry customers can be difficult, even for the most tenured agents. Using ASR, you can set a trigger for certain words or sentences (unhappy, unacceptable, complain, etc.) and escalate to the contact center supervisor or manager.
Compliance.
ASR technology can be useful in highly regulated industries, like banking, where agents must follow complex scripts and provide specific information to meet compliance and regulatory requirements. In this case, speech recognition is used to check if the agents follow the script and provide the customers with all the required information.
Real-time insights.
Speech analytics can examine and assess agents’ and customers’ tone and the topic of conversation, providing agents with prompts for better solving the issue. For example, if a customer complains about not being able to connect a new set of headphones to the computer. The system will identify the product (headphones) and the problem (bluetooth connection) and automatically prompt the agent with a troubleshooting guide.
On the other hand, the customer may be ordering a snowboard jacket for a ski trip. The system recognizes the category (ski apparel) and prompts the agent to complete the sale by introducing goggles and ski helmets in the conversation.
Authentication and self-service.
In banking customer service lines, ASR is commonly used to allow customers to authenticate and perform simple transactions, such as checking the balance, making a payment, or transferring funds reducing the average handle time in the contact center.
 
<h4></h4>
<h4>Fine-tuning ASR systems: make them learn from your agents.</h4>
Like any other AI model, ASR systems learn from high-quality data. Most models benefit more from small fine-tuning processes than from larger-scale changes.

Improving AI accuracy through continuous and incremental training with a cost-effective solution.

<h4>ASR systems are trained in two different ways:</h4>
<ul>
<li>Human tuning. Human programmers go through the logs of the ASR software and add the most commonly used words to its vocabulary.</li>
<li>Active learning. A much more sophisticated variant, where the software is programmed to learn by itself while being exposed to new vocabulary.</li>
</ul>
However, AI model accuracy in active learning can decrease over time. That’s why many technology giants (such as Facebook and Amazon) have in-house data scientists to maintain the predictive power of AI models.
Data scientists are expensive resources.  Most companies can’t afford to have a team of data scientists to improve their AI models. The answer lies in human-in-the-loop technology— a branch of AI that leverages human expertise to train and validate adjustments to AI models.

A simple no-code tool enables customer service agents to fine-tune the accuracy of AI models without the help of data scientists.

How human-in-the-loop technology empowers agents to operationalize AI

With human-in-the-loop technology, contact centers can have their own agents training, fine-tuning, and testing their ASR systems and other AI tools in a straightforward and cost-effective manner.
ASR is already an integral part of our life, whether in our houses or offices. Contact centers can now lean on ARS technology to streamline operations and improve efficiency at an affordable price.

Lídia Dias

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Learn what is ASR technology, how it enhances the customer experience, and how contact centers can implement it.

What is ASR technology and what are its advantages for the contact center?

What is the future of voice assistants?

The use of conversational AI in contact centers will be game-changing

How chatbots are changing—and improving—customer service

Training AI models: A better way

How human-in-the-loop technology empowers agents to operationalize AI

Lídia Dias

Other blog posts.

Bringing generative AI to healthcare through the contact center

5 benefits of an AI-powered insurance contact center solution

How artificial intelligence helps businesses modernize customer engagement

Should customer service leaders fear ChatGPT?

What is ASR technology and what are its advantages for the contact center?

What is the future of voice assistants?

The use of conversational AI in contact centers will be game-changing

How chatbots are changing—and improving—customer service

Training AI models: A better way

How human-in-the-loop technology empowers agents to operationalize AI

Lídia Dias

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Other blog posts.

Bringing generative AI to healthcare through the contact center

5 benefits of an AI-powered insurance contact center solution