Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Detecting and correcting speech reco...
~
Zollo, Teresa Mary.
Linked to FindBook
Google Book
Amazon
博客來
Detecting and correcting speech recognition errors during natural language understanding.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Detecting and correcting speech recognition errors during natural language understanding./
Author:
Zollo, Teresa Mary.
Description:
228 p.
Notes:
Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3920.
Contained By:
Dissertation Abstracts International64-08B.
Subject:
Computer Science. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3102312
Detecting and correcting speech recognition errors during natural language understanding.
Zollo, Teresa Mary.
Detecting and correcting speech recognition errors during natural language understanding.
- 228 p.
Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3920.
Thesis (Ph.D.)--The University of Rochester, 2003.
The focus of this work is to improve the ability of a spoken dialog system to identify and compensate for speech recognition errors. Rather than trying to eradicate errors coming from the speech recognizer, our work focuses on detecting, locating and correcting the errors that occur, within the natural language understanding component of a spoken dialog system.Subjects--Topical Terms:
626642
Computer Science.
Detecting and correcting speech recognition errors during natural language understanding.
LDR
:02808nmm 2200289 4500
001
1854538
005
20040615083623.5
008
130614s2003 eng d
035
$a
(UnM)AAI3102312
035
$a
AAI3102312
040
$a
UnM
$c
UnM
100
1
$a
Zollo, Teresa Mary.
$3
1942374
245
1 0
$a
Detecting and correcting speech recognition errors during natural language understanding.
300
$a
228 p.
500
$a
Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3920.
500
$a
Supervisor: Lenhart K. Schubert.
502
$a
Thesis (Ph.D.)--The University of Rochester, 2003.
520
$a
The focus of this work is to improve the ability of a spoken dialog system to identify and compensate for speech recognition errors. Rather than trying to eradicate errors coming from the speech recognizer, our work focuses on detecting, locating and correcting the errors that occur, within the natural language understanding component of a spoken dialog system.
520
$a
Current spoken dialog systems operate within narrow domains, and many work by filling in slots for the information they need to achieve a specific task. Such simple systems do not require a syntactic analysis of what the user said; they can accomplish their mission by recognizing only a few key phrases. We believe that as spoken language systems become more sophisticated, they will require a more thorough analysis of the user input, rendering many current robustness strategies ineffective. By identifying implausible speech recognition hypotheses, the spoken dialog system can attempt to repair the communication breakdown, either by using stochastic methods to predict what was actually said or by using an appropriate dialog strategy.
520
$a
We show that by describing the expected structure of spoken turns in human-computer practical dialog and formalizing the structure by means of context-free grammar rules used by a traditional bottom-up chart parser, we can achieve 92.1% accuracy in the task of detecting erroneous speech recognizer output based solely on the chart generated during parsing, an improvement of 18.2 percentage points over the majority-class baseline. Furthermore, we can reliably locate the start index of errors within misrecognized strings using the chart and domain-specific word bigram models. We developed and implemented algorithms that use the predicted error start location together with the word bigram models, phonetic similarity and the recognized string to generate correction hypotheses.
590
$a
School code: 0188.
650
4
$a
Computer Science.
$3
626642
650
4
$a
Health Sciences, Speech Pathology.
$3
1018105
690
$a
0984
690
$a
0460
710
2 0
$a
The University of Rochester.
$3
1249304
773
0
$t
Dissertation Abstracts International
$g
64-08B.
790
1 0
$a
Schubert, Lenhart K.,
$e
advisor
790
$a
0188
791
$a
Ph.D.
792
$a
2003
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3102312
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9173238
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login