Name
Abstract | ||
|---|---|---|
In this article we present an alternative method for defining the question set used for the induction of acoustic phonetic decision trees. The method is data driven and employs local similari- ties between the probability density functions of hidden Markov models. The method is shown to work at least as well as the standard method using question sets devised by human experts. |
Year | Venue | Field |
|---|---|---|
2004 | INTERSPEECH | Decision tree,Data-driven,Pattern recognition,Computer science,Speech recognition,Artificial intelligence,Hidden Markov model,Probability density function,Codebook |
DocType | Citations | PageRank |
Conference | 3 | 0.47 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frank Diehl | 1 | 3 | 0.80 |
| Asunción Moreno | 2 | 399 | 44.97 |