-
Books
-
Education
-
eBooks
-
Audio Books
-
Film & TV
-
Calendars, Diaries & Stationery
-
Giftshop
Browse through the navigation bar
-
Books
-
Education
-
eBooks
-
Audio Books
-
Film & TV
-
Calendars, Diaries & Stationery
-
Giftshop
Novel Techniques for Dialectal Arabic Speech Recognition
by Mohamed Elmahdy and others
$210.72
Spend another {0} to pay with
or 4 easy payments of $52.68 with
This item qualifies your order for FREE DELIVERY
Hardback
Pub: 12/02/2012
Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied… more to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers.
In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and Maximum A-Posteriori (MAP) to adapt existing phonemic MSA acoustic models with a small amount of dialectal ECA speech data. Speech recognition results indicate a significant increase in recognition accuracy compared to a baseline model trained with only ECA data. less
In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and Maximum A-Posteriori (MAP) to adapt existing phonemic MSA acoustic models with a small amount of dialectal ECA speech data. Speech recognition results indicate a significant increase in recognition accuracy compared to a baseline model trained with only ECA data. less
- ISBN:
- 9781461419051
- 9781461419051
- Category:
- Speech recognition
- Format:
- Hardback
- Publication Date:
- 12-02-2012
- Language:
- English
- Publisher:
- Springer-Verlag New York Inc.
- Country of origin:
- United States
- Pages:
- 110
- Dimensions:
- 235x155x9mm
- Weight:
- 0.37kg
This title is in stock with our Australian supplier and should arrive at our Sydney warehouse within 2 - 3 weeks of you placing an order.
Once received into our warehouse we will despatch it to you with a Shipping Notification which includes online tracking.
Please check the estimated delivery times below for your region, for after your order is despatched from our warehouse:
ACT Metro: 2 working days
NSW Metro: 2 working days
NSW Rural: 2-3 working days
NSW Remote: 2-5 working days
NT Metro: 3-6 working days
NT Remote: 4-10 working days
QLD Metro: 2-4 working days
QLD Rural: 2-5 working days
QLD Remote: 2-7 working days
SA Metro: 2-5 working days
SA Rural: 3-6 working days
SA Remote: 3-7 working days
TAS Metro: 3-6 working days
TAS Rural: 3-6 working days
VIC Metro: 2-3 working days
VIC Rural: 2-4 working days
VIC Remote: 2-5 working days
WA Metro: 3-6 working days
WA Rural: 4-8 working days
WA Remote: 4-12 working days
Reviews
This product has no reviews yet.
Thanks for reviewing Novel Techniques for Dialectal Arabic Speech Recognition. We will process your review. Accepted reviews will be posted within 3-7 business days.
You can find this item in:
You are buying a backorder title
×Be the first to know, stay up to date with what's trending and get staff picks in your inbox with our newsletter
Follow Us
Secured by:
Copyright 2025. All rights reserved.
Share This Book