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  1. IEEE Transactions on Speech and Audio Processing
  2. Year : 1996 Volume : 4
  3. Issue 6
  4. High-performance alphabet recognition
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Year : 2005 Volume : 13
Year : 2004 Volume : 12
Year : 2003 Volume : 11
Year : 2002 Volume : 10
Year : 2001 Volume : 9
Year : 2000 Volume : 8
Year : 1999 Volume : 7
Year : 1998 Volume : 6
Year : 1997 Volume : 5
Year : 1996 Volume : 4
Issue 6
An 8-kb/s conjugate structure CELP (CS-CELP) speech coder
Predicting unseen triphones with senones
Vocabulary independent discriminative utterance verification for nonkeyword rejection in subword based speech recognition
High-performance alphabet recognition
Conveying visual information with spatial auditory patterns
A statistical pattern recognition approach to robust recursive identification of nonstationary AR model of speech production system
Issue 5
Issue 4
Issue 3
Issue 2
Issue 1
Year : 1995 Volume : 3
Year : 1994 Volume : 2
Year : 1993 Volume : 1

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High-performance alphabet recognition

Content Provider IEEE Xplore Digital Library
Author Loizou, P.C. Spanias, A.S.
Copyright Year 1993
Abstract Alphabet recognition is needed in many applications for retrieving information associated with the spelling of a name, such as telephone numbers, addresses, etc. This is a difficult recognition task due to the acoustic similarities existing between letters in the alphabet (e.g., the E-set letters). This paper presents the development of a high-performance alphabet recognizer that has been evaluated on studio quality as well as on telephone-bandwidth speech. Unlike previously proposed systems, the alphabet recognizer presented is based on context-dependent phoneme hidden Markov models (HMMs), which have been found to outperform whole-word models by as much as 8%. The proposed recognizer incorporates a series of new approaches to tackle the problems associated with the confusions occurring between the stop consonants in the E-set and the confusions between the nasals (i.e., letters M and N). First, a new feature representation is proposed for improved stop consonant discrimination, and second, two subspace approaches are proposed for improved nasal discrimination. The subspace approach was found to yield a 45% error-rate reduction in nasal discrimination. Various other techniques are also proposed, yielding a 97.3% speaker-independent performance on alphabet recognition and 95% speaker-independent performance on E-set recognition, A telephone alphabet recognizer was also developed using context-dependent HMMs. When tested on the recognition of 300 last names (which are contained in a list of 50,000 common last names) spelled by 300 speakers, the recognizer achieved 91.7% correct letter recognition with 1.1% letter insertions.
Starting Page 430
Ending Page 445
Page Count 16
File Size 2228309
File Format PDF
ISSN 10636676
Volume Number 4
Issue Number 6
Language English
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date 1996-11-01
Publisher Place U.S.A.
Access Restriction Subscribed
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword Telephony Speech recognition Hidden Markov models Vocabulary Information retrieval Speech analysis Context modeling Testing Humans Costs
Content Type Text
Resource Type Article
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