Speech recognition use cases enable touchless collaboration

For companies bringing workers back to the office, touchless collaboration is key. These three speech recognition use cases can help make that transition easier.

Speech technology has evolved on many fronts, and among those use cases, workplace collaboration is one of the most interesting. Much of this innovation has been AI-based, with automation a key driver. While that rationale hasn't changed, COVID-19 has fueled another driver: the touchless economy. Every aspect of daily life is now being filtered through that lens, including the world of work, where speech technology has newfound value.

The abrupt shift to work from home has created new challenges for collaboration, and speech technology has played a central role in making this transition easier. For many, this is a new workstyle, and while some will prefer to stay in this mode, others look forward to a return to the workplace. Work from home isn't viable for everyone, and many jobs simply work much better in an office setting.

For businesses looking to bring workers back to the office, safety is paramount, and speech technology has a key role to play. Workers will have a variety of concerns around social distancing, minimizing touchpoints and sharing resources such as keypads or touchscreens. Let's examine three speech recognition use cases -- both endpoints and applications -- that IT should consider as companies evaluate their return-to-workplace plans.

1. Smart speakers

Devices such as the Amazon Echo and Google Home have become wildly popular among consumers, but these gadgets should also be considered prime endpoints for speech-based applications in the workplace. In fact, these voice-first devices will find even more utility when employees return to their office spaces.

It's not merely that smart speakers are well suited to a touchless workspace environment. Because they are AI-driven, these devices can take on more tasks as they learn users' behaviors. Good entry point use cases would include using voice commands to run a meeting or to employ real-time transcription to take notes during a meeting.

The abrupt shift to work from home has created new challenges for collaboration, and speech technology has played a central role in making this transition easier.

2. Voice biometrics

This is a rapidly evolving field, also largely driven by AI, which can now be used to enable workflows and collaboration. Biometrics takes many forms -- other modes, such as retina scans or fingerprinting, have been in use for years -- but voice has some distinct benefits that align well with a touchless workplace. This may not be evident to all IT decision-makers, and the key here is AI and its role in recognizing not just speech, but voice. It is biometric-based voice recognition -- and its ability to reliably verify personal identity -- that will have the most value for workspace collaboration.

Although voice biometrics is an application rather than an endpoint, its innovative use of speech helps improve productivity. Rather than, say, using contact-based forms of entry into buildings, elevators, offices or meeting rooms, voice biometrics can authenticate entry or access, both safely and quickly. The same holds true when using biometrics through a PC or a collaboration interface to join or run a meeting: Only your voice is needed for access and participation.

3. Speech to text

Like biometrics, this is an application, but among speech recognition use cases, it has great value for collaboration when used with any voice-enabled endpoint that has a keypad. Speech to text (STT) is one of many AI use cases that have become good enough now for everyday use in the workplace, and it's an ideal application for office- or home-based work. By nature, there are many instances where using a keypad isn't an option or is especially inconvenient, and as long as the output doesn't have to be 100% accurate, STT is an effective proxy.

Prime use cases would be to employ STT to dictate an email, reply to text messages, send alerts or requests for colleagues to join a meeting, or edit a document. With today's AI, all these applications can be voice-driven, and as the machine learning algorithms improve, STT will be viable for more complex tasks. On its own, STT has intrinsic value for driving productivity, but in the context for making workers more comfortable coming back to the office, it can become a key enabler for collaboration in a touchless workplace.

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