Voice recognition is the process by which a machine or program receives and interprets dictation as well as understands and carries out spoken commands. Voice recognition technologies helps customers comply with privacy, security, and safety requirements governed by law and by user expectations. Automatic voice recognition and text-to-speech software work together to voice-enable many applications. Software sales are expected to increase at a substantial rate during this period.
One of the major factors driving this market is that companies across all sectors, seeking a competitive edge that will differentiate them in an increasingly crowded business environment, want products that will help them retain as well as to grow their customers. Various industries such as airlines, banks, and brokerages depend on voice recognition functionality, not only to enhance their customer contacts, but also to comply with security requirements dictated by the law and the security conscious expectations of customers. One of the major factors restraining this market is that all voice recognition systems commit errors because of false inputs produced by barking dogs, screaming children, and loud external conversations.
The market has many opportunities as five years down the line it is expected that companies will pair voice recognition technologies with the latest research in augmented reality and artificial intelligence, creating a new generation of compelling products. Some of the key players in this market are 3M health information systems, Aurix, Cisco, Aspect communication corp., autonomy, Avaya Inc., IBM, Dragon Systems, Cyara solutions, Chant, Loquendo, Lumenvox, Micoautomation, and Contact Solutions, Inc.
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This research report analyzes this market depending on its market segments, major geographies, and current market trends. Geographies analyzed under this research report include
- North America
- Asia Pacific
- Europe
- Rest of the World
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- Market growth drivers
- Factors limiting market growth
- Current market trends
- Market structure
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