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A deep dive on speech-to-text and text-to-speech transcription, speech recognition, voice analytics, and more
Enterprises increasingly want to leverage the technology to process natural language -- i.e., our regular old speaking voices -- at cloud scale and turn those voices into structured data for analysis. Accordingly, a wide range of companies, from traditional industry players to Internet giants and startups alike, seek to deliver business value through speech technologies. This is about deriving value from human-to-machine interactions, and the list of offerings for the enterprise is long and growing, including everything from speech-to-text and text-to-speech transcription and translation services to voice recognition and voice analytics. But before you can figure out which of these offerings might serve your organizational use cases, you have to understand how these technologies work and how they're being packaged up for the enterprise. You'll come away from this session armed with knowledge you need to understand a variety of speech technologies.
What role do natural language processing/artificial intelligence, cloud computing, and big data analytics play in the rise of speech technologies for the enterprise?
What are the different types of speech technologies for the enterprise, and what are sample use cases for each?
What types of vendors provide speech technologies, through what sorts of services?
What are questions to ask potential vendors about how their speech products work?
Are these speech technologies all cloud based, or do any vendors offer premises versions?