Zillennials Use Speech More Often

The microgeneration known as Zillennials—those born between 1991 and 1999—are using voice technology more frequently than older age groups, particularly in areas like shopping, financial management, and obtaining information, according to a new report by PYMNTS.

Nearly two-thirds of Zillennials used voice assistants at home in the past year, 26 percent more than the general population, the research found.

Other findings from the research include the following:

• This generation is 18 percent more likely than others to use voice technology for tasks such as gathering information or verifying identities, with 68 percent reporting regular use.
• In retail, 55 percent of Zillennials used voice assistants for shopping and payments within the past year, a 34 percent increase compared to the total population. And 14 percent of Zillennials completed their transactions through voice alone, 35 percent higher than the general population, which only had 10 percent achieving the same result.
• Half of Zillennials used voice technology for financial tasks, surpassing the overall population by 34 percent.
• Twenty-seven percent of Zillennials used voice assistants to fully manage home-related tasks, and 15 percent completed financial tasks with voice assistance, 43 percent more likely than other age groups.
• Zillennials relied on voice technology to manage unexpected situations, such as scheduling conflicts or emergencies. When traffic might cause delays, 43 percent of Zillennials would use a voice assistant to adjust their schedules, 19 percent higher than the overall population.
• If faced with unexpected disruptions, such as running late for a doctor’s appointment, Zillennials would use voice technology to notify others or change plans; 41 percent would push back their reservations due to traffic, and 40 percent would have voice assistants notify family members if they needed help with pickups.
• Forty-eight percent of Zillennials would use voice assistants to reach out to family or friends in case of emergencies, such as after a car accident, 13 percent higher than the overall sample.

These results prompted analysts at PYMNTS to conclude that there is “a high adoption rate and a trend toward deeper engagement with voice technology, setting [Zillennials] apart from older generations like Millennials.”

New Speech Framework Improves Medical Outcomes

Research from several academics at institutions like Jouf University in Saudi Arabia, South Valley University in Egypt, and St. Mary’s College of California, found that enhancing intelligent speech technologies with federated learning, multilayer perception, and gated recurrent unit neural networks improved their transcription accuracy and their ability to correctly diagnose diseases and control medical equipment in smart hospitals.

This distributed approach, the research found, allowed speech technology models that were already infused with artificial intelligence and natural language processing capabilities to learn from diverse, real-world data while ensuring compliance with strict data protection standards. It resulted in accuracy of 98.6 percent, with consistently high sensitivity and specificity. It also enabled collaborative model training across multiple hospital sites, preserving patient privacy by avoiding raw data exchange.

Intelligent speech technology has transformed patient care in the contemporary healthcare system, but the promising results from these systems still have signi?cant limitations in their frameworks, especially concerning data privacy, processing speed, and adaptability to different clinical environments, the researchers also conclude, noting that most solutions today still struggle with real-time accuracy.

But at the same time, the researchers have a very positive outlook for their new framework.

“In the dynamic landscape of modern healthcare, the integration of intelligent speech technology represents a pivotal advancement poised to revolutionize patient care and hospital management. Its emergence marks a departure from static, siloed systems toward interconnected, intelligent ecosystems that prioritize ef?ciency, accuracy, and above all, patient-centricity,” their report says.

“This research underscores the transformative potential of federated learning and advanced neural networks for addressing pressing challenges in modern healthcare and setting the stage for future innovations in intelligent medical technology. As this technology continues to evolve and permeate every facet of the healthcare ecosystem, its transformative potential is boundless, unlocking new opportunities for innovation, collaboration, and ultimately, improved health outcomes for individuals and communities alike,” the researchers conclude.