Name
Abstract | ||
|---|---|---|
A modified hierarchical mixtures of experts (HME) architecture is presented for text-dependent speaker identification. A new gating network is introduced to the original HME architecture for the use of instantaneous and transitional spectral information in text-dependent speaker identification. The statistical model underlying the proposed architecture is presented and learning is treated as a maximum likelihood problem; in particular, an expectation-maximization (EM) algorithm is also proposed for adjusting the parameters of the proposed architecture. An evaluation has been carried out using a database of isolated digit utterances by 10 male speakers. Experimental results demonstrate that the proposed architecture outperforms the original HME architecture in text-dependent speaker identification. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1109/72.536325 | IEEE Transactions on Neural Networks |
Keywords | Field | DocType |
feature extraction,neural nets,speaker recognition,expectation-maximization algorithm,gating network,isolated digit utterances,male speakers,maximum likelihood problem,modified hierarchical mixtures of experts architecture,statistical model,text-dependent speaker identification | Speaker identification,Computer science,Speaker recognition,Artificial intelligence,Systems architecture,Artificial neural network,Architecture,Pattern recognition,Feature extraction,Speech recognition,Statistical model,Maximization,Machine learning | Journal |
Volume | Issue | ISSN |
7 | 5 | 1045-9227 |
Citations | PageRank | References |
19 | 1.61 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ke Chen | 1 | 750 | 60.37 |
| Dahong Xie | 2 | 42 | 5.34 |
| Huisheng Chi | 3 | 211 | 22.81 |