Global Vocal Biomarker Market is expected to grow at a CAGR of 23.30% between 2018 and 2027

Vocal Biomarkers Reforming Healthcare Diagnostics

Vocal patterns have been used by clinical psychologists and psychoanalysts for analyzing personality traits of patients, and helping creation of headway in clinical and medical investigations. Recent breakthroughs in the healthcare sector have led to the development of a unique diagnostic tool known as vocal biomarker, by combining the concept of biological markers with the aforementioned methodology to analyze personality traits.

These vocal biomarkers are deemed to have immense potential in diagnosing disease based on vocal cues. As part of ongoing breakthroughs, a group of researchers from the New York University Langone Medical Center is developing a machine learning-based artificial intelligence (AI) system that would be capable of analyzing various voice characteristics that include rhythm, tone, and pitch from patients.

Remote health monitoring potential of vocal biomarkers is also gaining high interest among researchers worldwide, For example, Beyond Verbal and Mayo Clinic have collaborated for discovering vocal patterns of patients suffering from coronary artery disease. A key concept backing the development is the impact of hardening of arteries on speech production. With advancements in technology, vocal biomarkers will soon be able to diagnose various diseases including certain cancers, Parkinson’s disease, and heart conditions.

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Leveraging Product Development to Enhance Collaboration

Product development prevails as an imperative strategy driving collaborating between leading companies and research institutes across various sectors, and healthcare is no exception, Apropos of vocal biomarkers, Beyond Verbal has developed “Beyond mHealth Research Platform”, which aims at collaborating with universities, businesses, hospitals, and research institutes for collectively developing unique vocal biomarkers.

Another leading player, Sonde Health Inc., has introduced voice-based technology platform that enables diagnosing and monitoring various conditions and diseases. The company has collaborated with Massachusetts Institute of Technology (MIT) for licensing the technology. Such collaborations and developments will lead to better solutions and more accurate results for patients. It will further encourage researchers and institutions worldwide in collecting voice data for disease diagnostics and improving outcome of patients.

Virtual Private Assistants Enabling Voice-based Emotion Detection

Current digital world is making rapid transformations in the way people interact with technology and one another, with virtual private assistants taking on a personalized experience. As virtual private assistants such as Amazon’s Alexa become more popular & useful and smarter, developers are focusing on providing them with additional tools that enable recognizing emotions. A prime example of such development is the cloud-based API engine by Beyond Verbal, which integrates with the virtual private assistants (VPAs).

The aim of Beyond Verbal’s project is to enhance the sensitivity of one’s connected home. Focus of this cloud-based API engine is directed toward eliminating VPAs’ emotional blind spots, given that the vocal intonations in human communication represent 35-40% of emotions conveyed. Future developments of vocal biomarkers is likely to enable VPAs analyze voice for the specific health conditions, providing unique insights into remote health monitoring and personalized tech.

A recently compiled report of Fact.MR envisages the global vocal biomarker market to record a spectacular 23.3% CAGR between the forecast period 2018 and 2027. Revenues from global sales of vocal biomarkers are foreseen to surpass US$ 390 Mn by 2027-end. Beyond Verbal, Sonde Health, IBM Corporation, and other leading participants operating in the global vocal biomarker market have been profiled and analyzed in detail in the report.

Report Analysis at https://www.factmr.com/report/719/vocal-biomarker-market

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