Voice - The next computing platform - Global Thematic Research
Many of us will be talking increasingly to machines. Products such as smartphones, in-car infotainment systems, biometric ID systems, home speakers, games consoles, televisions, doors, fridges and industrial machines are already, or will soon become, conversational.
Speech recognition technology is currently about 90% accurate. In order for voice-activated products to go mainstream, speech recognition needs to reach 99% accuracy. This may take until 2030. But, in the meantime, investors need now to factor voice-driven AI into their thinking and into the way they assess the future prospects of many of their mid-term investments.
Inside this report, we look at the key players impacted by this theme, drilling down into the value chain and identifying winners and losers.
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- GlobalData has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, GlobalDatas thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, GlobalData tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores. The algorithms in GlobalDatas thematic engine help to clearly identify the winners and losers within the TMT sector. Our 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. Our thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Single Theme report, offering in-depth research into a specific theme. It identifies winners and losers based on technology leadership, market position and other factors.
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EVOLUTION OF VOICE TECHNOLOGY
Where are we in the evolution of voice technology?
Voice platforms are approaching take off point
so investors need to factor voice-driven AI into their thinking
Chinas role in voice platforms could be big
Voice algorithms are still only 90% accurate
The evolving business context around voice
Application programming interfaces
Voice-driven platforms and devices
A VOICE TECHNOLOGY TIMELINE
Voice by the numbers
Hidden Markov Models dominate speech recognition
while Connectionist models created the concept of artificial neural networks
Now the focus is on deep learning
What the future holds for voice
Privately held companies
APPENDIX: OUR THEMATIC RESEARCH METHODOLOGY
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