- Home
- Language Arts & Disciplines
- Linguistics
- Statistical Methods for Speech Recognition - 9780262546607
Statistical Methods for Speech Recognition - 9780262546607
List Price:
$65.00
- Availability: Confirm prior to ordering
- Branding: minimum 50 pieces (add’l costs below)
- Check Freight Rates (branded products only)
Branding Options (v), Availability & Lead Times
- 1-Color Imprint: $2.00 ea.
- Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
- Belly-Band Wrap: $2.50 ea. (full-color printed)
- Set-Up Charge: $45 per decoration
- Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
- Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
- Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
- RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
Product Details
Author:
Frederick Jelinek
Format:
Paperback
Pages:
306
Publisher:
MIT Press (November 1, 2022)
Language:
English
ISBN-13:
9780262546607
ISBN-10:
0262546604
Weight:
13oz
Dimensions:
6" x 9"
File:
RandomHouse-PRH_Book_Company_PRH_PRT_Onix_full_active_D20260405T165002_155746777-20260405.xml
Folder:
RandomHouse
List Price:
$65.00
Series:
Language, Speech, and Communication
Case Pack:
24
As low as:
$50.05
Publisher Identifier:
P-RH
Discount Code:
A
QuickShip:
Yes
Audience:
General/trade
Country of Origin:
United States
Pub Discount:
65
Imprint:
The MIT Press
Overview
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques.
Bradford Books imprint








