Natural Language Processing vs Speech Recognition

Developers should learn NLP when building applications that involve text or speech data, such as chatbots, virtual assistants, content recommendation systems, or automated customer support meets developers should learn speech recognition for building voice-controlled interfaces, such as virtual assistants (e. Here's our take.

Natural Language Processing

Nice Pick

Developers should learn NLP when building applications that involve text or speech data, such as chatbots, virtual assistants, content recommendation systems, or automated customer support

Pros

• It is essential for tasks like sentiment analysis in social media monitoring, machine translation in global platforms, or information extraction from documents in legal or healthcare domains
• Related to: machine-learning, deep-learning

Cons

• Specific tradeoffs depend on your use case

Speech Recognition

Developers should learn speech recognition for building voice-controlled interfaces, such as virtual assistants (e

Pros

• g
• Related to: natural-language-processing, machine-learning

Cons

• Specific tradeoffs depend on your use case

The Verdict

These tools serve different purposes. Natural Language Processing is a concept while Speech Recognition is a technology. We picked Natural Language Processing based on overall popularity, but your choice depends on what you're building.

The Bottom Line

Natural Language Processing wins

Based on overall popularity. Natural Language Processing is more widely used, but Speech Recognition excels in its own space.