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Table of contents
  • 1. Course readings
  • 2. Material on project topics
    • 2.1. Language model adaptation
    • 2.2. Audio event tagging
    • 2.3. Language recognition
    • 2.4. Speech command recognition
    • 2.5. Language Modeling for Indian Languages
    • 2.6. Automatic detection of alcohol intoxication
    • 2.7. Speech adaptation
    • 2.8. Speaker adaptation
    • 2.9. Deep denoising autoencoder for speech enhancement
    • 2.10. Native language recognition
    • 2.11. Chatbots
    • 2.12. Comparing subword language models
    • 2.13. Speaker recognition
    • 2.14. Voice activity detection
    • 2.15. DNNs for acoustic modeling
    • 2.16. Connectionist temporal classification
    • 2.17. Attention-based ASR
    • 2.18. Data augmentation
    • 2.19. Speech synthesis
    • 2.20. Speech compression
    • 2.21. Speech recognition in noise
    • 2.22. Confidence measures for ASR
    • 2.23. Features for ASR
    • 2.24. Multichannel ASR
    • 2.25. Pronunciation model adaptation
    • 2.26. Audio indexing

ELEC-E5510 - Speech Recognition D, Lecture, 26.10.2022-9.12.2022

This course space end date is set to 09.12.2022   Search Courses: ELEC-E5510

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Reading materials

Completion requirements

Collection of reading materials by topic.

2. Material on project topics

2.14. Voice activity detection

  • J. Ramírez, J. M. Górriz and J. C. Segura. Voice Activity Detection. Fundamentals and Speech Recognition System Robustness
  • Christian Uhle, book editor: Tom Bäckström Voice Activity Detection. Chapter 13 in Speech Coding (available as E-book)

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