In the world that we live in today, communicating with various appliances has become the norm thanks to the continuous development of automated speech recognition technology, also known as ASR, computer speech recognition, or speech-to-text.

ASR is a technology that can identify and process human voices into text. In the last decade, this field has advanced exponentially, with ASR systems prevalent in almost all the devices and applications we use daily, such as Siri, Google Assistant, Amazon’s Alexa, TikTok, and Instagram for real-time captions, and more. Similarly, this technology is also used in smart home tech, in-car command systems, and more.

This modern technology is sophisticated enough to understand the context and nuance of human language and has permanently changed how we interact with our devices. Hence this blog will delve into the various uses of ASR thus far and provide a comprehensive overview of its pros and cons.

Uses of ASR

A variety of speech recognition technology can assist in the day-to-day processes, helping businesses and customers save a great deal of time. Let us look at some of the primary uses of automated speech recognition, including:

• ASR is used for dictation: Professionals across industries and students utilize ASR for dictating virtual meetings, which can be transcribed. Using this technology can save time and ensure that the transcribed document has all the accurate information.

In addition, ASR can be used for personal use to dictate shopping lists, action items, a reminder, and record anything else that a user would want to make a note of.

• Accessibility: A voice recognition system can also work in reverse; instead of translating speech into text, you can translate text into speech. This feature, available on several platforms, has proven helpful for individuals with speech and sight problems.
• Automotive: Driver safety has significantly improved since the introduction of voice-activated navigation systems and car search capabilities. The introduction of this software has drastically reduced road accidents worldwide.
• Sales: Calls made to call centers can now be transcribed to identify call patterns or issues using ASR. Additionally, ASR technology enables cognitive bots to communicate with real-time users on web pages to answer queries or solve requests without human intervention.

Pros of ASR

Automated speech recognition, since its introduction, has proven to be very helpful in various scenarios. Given below are some pros of ASR:

• Since most people tend to talk faster than they can write, voice recognition makes it easier to note down speech without the added stress of writing or typing. Not only does it also saves people from having to read illegible handwriting, but it also reduces the document’s turnaround time.
• By utilizing speech recognition software, users are less likely to produce documents riddled with errors. Furthermore, in most cases, various recently created new applications can deliver consistent, accurate outputs.
• Professionals from various industries now have the flexibility to work in or away from the office. In addition, these professionals also have the flexibility to share files with multiple devices on a network.
• Various mundane jobs can now be streamlined and simplified using ASR.
• Setting up conference calls, meetings, reminders, and many other tasks is faster through voice recognition, leading to increased efficiency and productivity.
• The integration of ASR also makes acquiring information about a specific project or subject much faster than done manually.

Cons of ASR

Although there are several pros to using ASR technology, there are also specific challenges that you must understand:

• Different industries tend to use jargon, which is not always easily understood by people or by the automatic speech recognition software.
• Transcripts related to the medical industry need to be as accurate as possible, and although ASR is exceptionally advanced, it cannot guarantee the maximum possible accuracy. Hence, the accuracy is not entirely reliable.
• ASR needs to be trained to understand and recognize the speaker’s voice which may take some time.
• Voice data used for ASR has to be recorded, which has caused fear among its users as it may impact their privacy.
• ASR can misinterpret words if they are not dictated directly into the microphone.
• The accuracy of some speech recognition technology drops as sometimes, it cannot transliterate words spoken when they are spoken too quickly or by someone with an accent.

Conclusion

Voice recognition technology is still a growing trend that many people and companies have started to embrace. And although its evolution and improvement are still ongoing, it is essential to remember that voice technology is slowly proving that it can provide a wide range of benefits that make our lives easier.