Paper Info
Title
Automatic phoneme alignment based on acoustic-phonetic modeling
Abstract
This paper presents a method for speaker-independent automatic phonetic alignment that is distinguished from standard HMM-based "forced alignment" in three respects: (1) specific acoustic-phonetic features are used, in addition to PLP features, by the phonetic classifier; (2) the units of classification consist of distinctive phonetic features instead of phonemes; and (3) observation probabilities depend not only on the current state, but also on the state transition information. This proposed method is compared with a state-of-the-art baseline forced- alignment system on a number of corpora, including telephone speech, microphone speech, and children's speech. The new method has agreement of 92.57% within 20 msec on the TIMIT corpus, which is a 26% reduction in error over the baseline method (with 89.95% agreement on TIMIT). Average reduction in error over all corpora is 28%.
Year
Venue
Keywords
2002
INTERSPEECH
state transition
Field
DocType
Citations 
TIMIT,Pattern recognition,Computer science,Speech recognition,Artificial intelligence,Classifier (linguistics),Hidden Markov model,Microphone
Conference
10
PageRank 
References 
Authors
0.77
9
1
Name
Order
Citations
PageRank
John-Paul Hosom123123.43