The ability to get work done with nothing but your voice once seemed like something out of an episode of The Jetsons, but advancements in speech technology are changing people's perceptions. The use cases for speech technology are expanding, and the integration of AI with speech technology applications is changing the ways that organizations can use the technology.
Not all vendors offer the same integrations and applications for speech technology, so it's beneficial to determine your business goals for speech technology before deployment. Read on to learn what use cases are driving speech technology today and what future use cases could look like.
What are the primary use cases for speech technology?
Most early iterations of speech technology applications involved interactive voice response (IVR). IVR is often used in call centers to collect customer information and route calls to the appropriate agent. Due to the prerecorded nature of IVR, the technology is limited in how much it can automate a task. Speech technology can improve IVR by using vocal commands to sort through the prerecorded responses when directing calls.
Chatbots are another way to help collect data and route a call or query to the appropriate recipient. Chatbots offer additional benefits, such as the ability to look for and extract keyword information with vocal commands, making it easier for agents to comb through large quantities of information.
Outside of the contact center, personal digital assistants are a popular use case for speech technology applications. Most operate with a simple command-to-action format, allowing voice commands to complete tasks such as updating calendars, initiating conference calls and dictating email.
How does AI integrate with speech technology applications?
The addition of AI has rapidly expanded the capabilities of speech technology, and applications may have speech recognition functions on top of simple command-to-action functions.
With speech recognition, AI can analyze a conversation for emotional markers to help create a better customer experience by providing a call center agent with more contextualized data. For example, if a customer sounds angry or frustrated, AI-powered speech recognition software could prompt the agent to escalate the call to a supervisor.
AI enhancements to speech technology applications are primarily intended to enhance productivity. AI-based speech recognition is nearly at the same level as human speech, according to industry experts, which can expand the capabilities for both text-to-speech and speech-to-text applications.
AI is able to provide a new level of accuracy and context with the ability to recognize dialects, speech patterns and company names for smoother machine-to-human interactions. For example, instead of a digital assistant that simply adds an appointment to your calendar, an AI-driven digital assistant, such as Google Duplex, can call and make the appointment for you. As AI enhanced speech technology applications mature, more capabilities and use cases will emerge.