Aligning Text and Phonemes for Speech Technology Applications Using an EM-Like Algorithm
نویسندگان
چکیده
منابع مشابه
Aligning letters and phonemes for speech synthesis
A common requirement in speech technology is to align two different symbolic representations of the same linguistic ‘message’. For instance, we often need to align letters of words listed in a dictionary with the corresponding phonemes specifying their pronunciation. As dictionaries become ever bigger, manual alignment becomes less and less tenable yet automatic alignment is a hard problem for ...
متن کاملAligning phonemes using finte-state methods
The paper presents two finite-state methods which can be used for aligning pairs of cognate words or sets of different allomorphs of stems. Both methods use weighted finite-state machines for choosing the best alternative. Individual letter or phoneme correspondences can be weighted according to various principles, e.g. using distinctive features. The comparison of just two forms at a time is s...
متن کاملEM Clustering Algorithm for Automatic Text Summarization
Automatic text summarization has emerged as a technique for accessing only to useful information. In order to known the quality of the automatic summaries produced by a system, in DUC 2002 (Document Understanding Conference) has developed a standard human summaries called gold collection of 567 documents of single news. In this conference only five systems could outperforms the baseline heurist...
متن کاملAn EM-like Algorithm for Motion Segmentation via Eigendecomposition
This paper presents an iterative maximum likelihood framework for motion segmentation via the pairwise checking of pixel blocks. We commence from a characterisation of the motion blocks in terms of a matrix of pairwise similarity weghts for their motion vectors. The eigenvectors of this similarity weight matrix represent the initial pairwise clusters, i.e the independant motions present in the ...
متن کاملImproving Binary Text Classification Using the EM Algorithm
When we apply binary classification to multi-class classification for text classification, we use the One-Against-All method generally. However, this One-Against-All method has a problem. That is, the documents of a negative set are not labeled manually while those of a positive set are labeled by human. In this paper, we propose that the Sliding Window technique and the EM algorithm are applie...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Speech Technology
سال: 2005
ISSN: 1381-2416,1572-8110
DOI: 10.1007/s10772-005-2166-6