عنوان

Novel Techniques for Dialectal Arabic Speech Recognition

شابک

:9781461419051

شابک اشتباه

9781461419068 (e-ISBN)

شابک اشتباه

1461419069 (e-ISBN)

شماره

36313

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

عنوان اصلي

Novel Techniques for Dialectal Arabic Speech Recognition

نام عام مواد

[electronic resources]

نام نخستين پديدآور

\ Mohamed Elmahdy, Rainer Gruhn, Wolfgang Minker

محل نشرو پخش و غیره

New York

نام ناشر، پخش کننده و غيره

: Springer

تاریخ نشرو بخش و غیره

, 2012

نام خاص و کميت اثر

xxi, 110p.

ساير جزييات

:ill.

ابعاد

;24 cm.

متن يادداشت

Index

متن يادداشت

Bibliography

متن يادداشت

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 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--

موضوع مستند نشده

Automatic speech recognition

موضوع مستند نشده

Arabic language

موضوع مستند نشده

صدا -- تشخیص کامپیوتری

موضوع مستند نشده

زبان عربی

شماره رکورد غير از شماره رده بندي

مستند نام اشخاص تاييد نشده

Elmahdy, Mohamed

مستند نام اشخاص تاييد نشده

Gruhn, Rainer

مستند نام اشخاص تاييد نشده

Minker, Wolfgang

کشور

ایران

تاريخ عمليات

20191210084136.0

تاريخ و ساعت مذاکره و دسترسي

9781461419051.pdf

نوع ماده

BL

کد کاربرگه

279177

پیشوند ISBD اعمال شده است

1

تكميل شده

N