Introduction: Why text and speech data analysis is so important
When I consider how much information we consume and produce every day in the form of text and speech, it quickly becomes clear: Our world is data-driven. From emails and social media posts to customer reviews and support requests – text and speech data are everywhere. But why is it so important? Quite simply because it often reflects unspoken opinions, needs, and trends.
I'm also aware that this data represents a real treasure if we analyze it correctly. Companies can, for example:
- Assess customer satisfaction by evaluating feedback.
- Identify market trends by analyzing news and social media.
- Make processes more efficient by understanding internal communication patterns.
And that’s just the tip of the iceberg!
AI in Practice: How Machines Understand Language and Text
When I think about how machines understand our language, I'm always fascinated. It all starts with natural language processing (NLP), the ability of machines to analyze human language and make sense of it. They rely on two core techniques:
- Statistical models : Machines learn patterns and probabilities from vast amounts of text data. This is how they understand grammar, syntax, and context.
- Neural networks : This is where things get exciting – deep learning processes language semantically. This allows machines to recognize not only words but also their meaning.
The most exciting thing? Algorithms adapt automatically the more data they process.
