Name
Abstract | ||
|---|---|---|
This paper presents a study of the attractor variation in the reconstructed phase spaces of isolated phonemes. The approach is based on recent work in time-domain signal classification using dynamical signal models, whereby a statistical distribution model is obtained from the phase space and used for maximum likelihood classification. Two sets of experiments are presented in this paper. The first uses a variable time lag phase space to examine the effect of fundamental frequency on attractor patterns. The second focuses on speaker variability through an investigation of speaker-dependent phoneme classification across speaker sets of increasing size. The results are discussed at the end of the paper. |
Year | Venue | Keywords |
|---|---|---|
2003 | NOLISP | fundamental frequency,phase space,statistical distribution,time domain |
Field | DocType | Citations |
Time lag,Attractor,Distribution model,Fundamental frequency,Pattern recognition,Computer science,Phase space,Speech recognition,Signal classification,Artificial intelligence,Maximum likelihood classification | Conference | 1 |
PageRank | References | Authors |
0.45 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinjin Ye | 1 | 96 | 6.41 |
| Michael T. Johnson | 2 | 435 | 53.51 |
| Richard J. Povinelli | 3 | 225 | 20.40 |