Speech is the most common means of human communication, defined as the expression of thoughts and feelings through the articulation of sounds, in other words, through voice.

Obviously, through speech, we can communicate much faster. While a person can type an average of 40 words per minute, they can speak 160 words in the same timeframe.

However, it’s not just about numbers. While we speak, certain factors can make a big difference in the listener’s understanding: context, tone of voice, slang, etc.. Not to mention the audience and the language being spoken.

Human speech, which for us is natural and a skill we learn from childhood, is quite complex for machines, even those equipped with Artificial Intelligence.

From the 1950s to now, speech recognition systems have evolved significantly, especially with the advent of technologies like Machine Learning and Deep Learning, for example.

Technologies like Alexa, Google Home, Siri, Cortana, among others, emerged to make our interactions with machines easier, changing the way we shop, for instance.

And in this scenario, ASR appears.

What is ASR?

ASR (Automatic Speech Recognition) is a technology that allows speech recognition software to analyze sounds and transcribe them into text.

An Automatic Speech Recognition (ASR) system simulates a human listener, listening, understanding, and responding to what is spoken, converting sound into text. In other words, transforming speech into words.

When capturing sound, ASR translates the vibrations emitted by the voice, transforming them into text that can be understood by various software and hardware, thus simulating a human conversation.

This technology is increasing the speed and efficiency of customer service for companies and enhancing the experience of customers who are increasingly demanding and impatient.

ASR is a feature that speeds up the work of human agents, freeing them up for more strategic activities. It is essential in call centers when integrated with automated service systems like IVRs and voicebots.

How does it work?

Basically, ASR consists of voice recognition software and a hardware component, which in this case is the microphone.

First, we speak on the phone, or through a smartphone or virtual assistant like Alexa, for example. Then, the microphone on these devices captures our voice and creates a digital file.

This file stores our words, where noise is removed, and volume is equalized. Next, these sound waves are divided into phonemes. Finally, ASR technology analyzes and deduces words to form texts. All this, of course, happens in milliseconds.

Once the text is obtained, another component similar to chatbots, called NLP (Natural Language Processing), comes into play to infer the semantics or meaning of the text, typically understood as the intent and entity/entities pair.

What are its components?

Now that you know what it is and how it works, let’s explore the components an ASR system is generally composed of:

Digital representation: A method to extract the input (speech).

Speech extraction: This component identifies speech and transforms it into acoustic parameters.

Database: Acts as a voice library with annotations and transcriptions, essential for covering varied speech patterns.

Acoustic models: Identifies the speech waveform and divides it into small fragments, predicting the most likely phonemes in the speech.

Phonetic models: Identifies sounds and converts them into words, associating them with their phonetic representations.

Linguistic models: Here, the identified words are turned into sentences with the most likely sequence.

Algorithms: Also known as decoders, this component combines predictions from acoustic and linguistic models, generating the most probable transcriptions for each speech.

In summary, these are the components of ASR.

But it’s important to remember that along with all this, there are numerous peculiarities in human speech like accents, slang, as well as the speaker’s age, gender, and even mood, which make Automatic Speech Recognition (ASR) a more complex equation.

Nonetheless, when properly implemented under the supervision of a multidisciplinary team dedicated to the technology’s evolution, this feature can optimize customer service and relationships.

In today’s world, where most interactions are digital, this is an innovative system that can add significant value to companies.

What are the benefits for companies?

Now that you know what ASR is, how it works, and its components, let’s look at some benefits for your business:

• Reduced need for human intervention
• Lower staffing costs
• Optimized human service
• Freeing agents for strategic activities
• Automation of service processes
• Increased self-service efficiency
• Speech analysis (Speech Analytics)
• Enhanced customer experience
• Increased customer satisfaction
• Vocal imprint authentication, avoiding the need to memorize passwords
• Sentiment analysis (satisfaction vs. frustration)

And so on! These are just some of the main advantages. To leverage all these and more, you need to implement ASR in your business as soon as possible.

We hope you enjoyed the content. See you next time!

Also read: Should the bot’s persona always be female?