LONDON, June 9, 2016 /PRNewswire/ --
Advances in Automotive Voice Recognition Market : Virtual Assistant, Voice Biometrics and Deep Learning are the Key Disruptors in the Automotive Voice Recognition Market
Voice Recognition (VR) technology is primarily focused only on infotainment use cases. However, Original Equipment manufacturers (OEMs) and Tier-I suppliers are significantly investing in biometric and machine learning technologies. Even though OEM's are trying to adopt cloud-based and hybrid solutions, they are still dependent on embedded solutions as a back-up option, as hybrid and cloud-based solutions are facing infrastructure and security challenges. This report presents an analysis of the automotive voice recognition market and identifies the growth potential of various market segments. It also provides an overview of the level of OEM involvement in the voice recognition space and profiles key technology enablers.
Although constant improvements in VR technologies are being carried out with an aim to improve safety and brand differentiation, reduction in the latency time between command and reply is still a key concern.
Automotive Voice Recognition Market: Key Findings, Global, 2015
Voice Recognition (VR) technology is focused only on infotainment use cases. However, Original Equipment Manufacturers (OEMs) and Tier-I suppliers are significantly investing in biometric and machine learning technologies.
Premium OEMs are highly interested in Virtual Voice Assistant technology, as it is a brand differentiator and offers high customer comfort and convenience. Virtual Voice Assistant is offered by SIRI, Cortana, and Maluuba.
Tier-I suppliers act as technology integrators and do not have any proprietary technology of their own. Tier-I suppliers are getting involved in more joint ventures (JVs). For instance, HERE partnered with Nuance and NNG joined with iNAGO.
Although Nuance is leading the market in voice recognition technology, new entrants such as iNago and Sensory are proving to be technology disruptors.
Even though OEM's are trying to adopt cloud-based and hybrid solutions, they are still dependent on embedded solutions as a back-up option, as hybrid and cloud-based solutions are facing infrastructure and security challenges.
Key Questions this Study will Answer
• What are the various use-cases with voice recognition technology in cars?
• Does voice biometrics have a promising future within in-car operations?
• What are the various trends related to voice recognition with the advent of autonomous cars?
• What are the supplier capabilities and interest levels towards implementing voice recognition in automotive vehicles?
• What are the research and development (R&D) capabilities and future investment of technology enablers for voice recognition?
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