General Audio Signal Processing with Deep Learning
-
GET 12% OFF
- Publisher's listprice EUR 192.59
-
79 876 Ft (76 073 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 12% (cc. 9 585 Ft off)
- Discounted price 70 291 Ft (66 944 Ft + 5% VAT)
70 291 Ft
Availability
Not yet published.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Publisher Springer Nature Singapore
- Date of Publication 10 May 2026
- Number of Volumes 1 pieces, Book
- ISBN 9789819508358
- Binding Hardback
- No. of pages702 pages
- Size 235x155 mm
- Language English
- Illustrations XXV, 702 p. 185 illus., 176 illus. in color. 700
Categories
Long description:
Dive into the cutting-edge integration of deep learning with audio signal processing in this authoritative guide. Designed for audio engineers, data scientists, and tech enthusiasts, this book demystifies the complex world of deep neural networks, including CNNs and RNNs, and their applications in speech recognition, music transcription, and sound event detection.
Explore the practical side of deep learning with hands-on tutorials using TensorFlow and PyTorch, building your intuition for model architectures and hyperparameter tuning. Gain insights into real-world deployment challenges, from data preprocessing to model evaluation, interpretability, and scalability. Industry case studies and best practices illuminate the path to building efficient and effective deep learning-based audio systems.
This book empowers you with the knowledge to leverage the full potential of deep learning in audio processing, offering a comprehensive resource for tackling sophisticated audio tasks. Whether you're a researcher, engineer, or enthusiast, this guide is your key to mastering the synergy of audio signal processing and deep learning, ensuring you approach audio-related challenges with confidence and proficiency.
MoreTable of Contents:
"
""Chapter1-Introduction"".- ""Chapter2-Traditional Representation of Audio Signals"".- ""Chapter3-Machine Learning Methods for Audio Signals"".- ""Chapter4-Semi-Supervised Learning for Audio Signal"".- ""Chapter5-Self-Supervised Learning for Audio Signal"".- ""Chapter 6: Active Learning for Audio Signal"".- ""Chapter 7: Incremental Learning for Audio Signal Processing"".- ""Chapter 8: Few-Shot Learning for Audio Signal Processing"".- ""Chapter 9: Data Augmentation for Audio Signal"".- ""Chapter 10: Audio Classification"".- ""Chapter 11: Sound Source Localization"".- ""Chapter 12: Anomalous Sound Detection"".- ""Chapter 13: Audio Source Separation"".- ""Chapter 14: Audio Generation"".- ""Chapter 15: Audio-language Learning"".- ""Chapter 16: Audio-visual Signal Analysis"".- ""Chapter 17: Audio super-resolution"".- ""Chapter 18: EEG Auditory Decoding"".- ""Chapter 19: Audio Denosing"".- ""Chapter 20: Underwater Acoustics"".- ""Chapter 21: Urban Sound"".- ""Chapter 22: Industry Sound"".- ""Chapter 23: Medical Sound"".- ""Chapter 24: Bioacoustics"".- ""Chapter 25: Future Perspective"".
" More
