Speech Recognition in Natural Language Processing

Speech recognition, also known as automatic speech recognition (ASR), is a critical component of natural language processing (NLP) that converts spoken language into text. It enables machines to understand and interpret human speech, serving as the foundation for voice assistants, transcription tools, and more.

Key Technologies

  • Acoustic Models: Map audio signals to phonetic units (e.g., Speech_Recognition models).
  • Language Models: Predict word sequences using statistical methods.
  • Deep Learning: Modern systems often employ neural networks like RNNs or Transformers (e.g., Transformer_Model for sequence modeling).

Applications

  • Voice-to-text transcription 🎧
  • Smart assistants (e.g., Alexa, Siri) 🤖
  • Call center automation
  • Accessibility tools for the hearing impaired

Learn More

For an in-depth tutorial on implementing speech recognition, visit speech_recognition_tutorial.

Speech_Recognition
Transformer_Model