menu
{ "item_title" : "Machine Learning for Speaker Recognition", "item_author" : [" Man-Wai Mak", "Jen-Tzung Chien "], "item_description" : "This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/10/842/812/1108428126_b.jpg", "price_data" : { "retail_price" : "130.00", "online_price" : "130.00", "our_price" : "130.00", "club_price" : "130.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning for Speaker Recognition|Man-Wai Mak

Machine Learning for Speaker Recognition

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.

This item is Non-Returnable

Details

  • ISBN-13: 9781108428125
  • ISBN-10: 1108428126
  • Publisher: Cambridge University Press
  • Publish Date: November 2020
  • Dimensions: 9.8 x 7.7 x 0.7 inches
  • Shipping Weight: 1.7 pounds
  • Page Count: 334

Related Categories

You May Also Like...

    1

BAM Customer Reviews