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A novel stochastic deep resilient network for effective speech recognition.

Shilpi Shukla1, Madhu Jain2

  • 1Department of Electronics and Communication Engineering, Mahatma Gandhi Mission's College of Engineering & Technology, Noida, India.

International Journal of Speech Technology
|May 31, 2021
PubMed
Summary

This study introduces a novel stochastic deep resilient network (SDRN) for accurate speech recognition. The SDRN, optimized with a neural-based opposition whale optimization algorithm (NOWOA), achieves high accuracy for both isolated and continuous speech signals.

Keywords:
Deep neural networkOpposition whale optimization algorithmOptimizationSpeech recognitionStochastic deep resilient network

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Signal Processing

Background:

  • Speech recognition systems often face challenges with accuracy and computational efficiency.
  • Existing deep learning models require significant optimization for real-time applications.

Purpose of the Study:

  • To propose a novel stochastic deep resilient network (SDRN) for enhanced speech recognition.
  • To optimize the network using a neural-based opposition whale optimization algorithm (NOWOA) for improved performance.

Main Methods:

  • Developed a deep neural network (DNN) for speech signal classification.
  • Integrated NOWOA to optimize DNN hidden layers and neurons, reducing computation time.
  • Trained and tested the SDRN using standard databases and real-time recorded data.

Main Results:

  • Achieved 99.6% accuracy for isolated words (standard database) and 98.1% for real-time isolated words.
  • Attained 98.7% accuracy for real-time continuous speech signals.
  • Demonstrated superior performance of the SDRN compared to existing speech recognition techniques.

Conclusions:

  • The proposed SDRN, utilizing NOWOA optimization, significantly enhances speech recognition accuracy.
  • The method is effective for both isolated and continuous speech, including real-world conditions.
  • SDRN presents a promising advancement in the field of speech recognition technology.