What’s Your NLP Data Strategy

What’s Your NLP Data Strategy?

At the Conversational Interaction Conference earlier this month, attendees converged to learn about the latest developments in devices and applications that interact with text or speech in natural language, and how to take advantage of this growing trend. Representatives from financial services, entertainment, automotive firms and more heard from experts on where the industry is headed. While many exciting developments have occurred in this space, there is still room to improve the consumer experience with chat bots, digital assistants and other natural language-based technologies.

In a session entitled “Why the Voice of Your Customer is the Most Important Data You’ll Ever Analyze”, Stephen Fletcher from Artificial Solutions shared some interesting stats on the usage of voice-based assistants. According to their recent global research study:

  • 68% of respondents use a voice assistant service
  • 2 out of 3 users say they use their voice assistant service every week
  • Usage of voice-based assistants is growing at 49%
  • Uses for voice based technology include in-home, travel, banking, and in-car

In his presentation, Fletcher explained that while every enterprise has a Big Data strategy, few have an Natural Language Processing (NLP) data strategy. There is a wealth of customer data that needs to be analyzed in order to create a more personalized customer experience. Speech data communicates consumer values, and by better understanding those values, firms can create a stronger connection with customers. However, this data is unstructured and needs to be tagged for machine learning systems to use it effectively.

Appen specializes in converting unstructured data to structured data, whether the data is speech, search results or content. We work with the largest technology firms in the world to provide high quality data for digital assistants, voice recognition systems and more. Contact us today to discuss your data annotation needs.

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