Abstract
Today's state-of-the-art speech recognition systems typically use continuous density hidden Markov models with mixture of Gaussian distributions. Such speech recognition systems have problems; they require too much memory to run, and are too slow for large vocabulary applications. Two approaches are proposed for the design of compact acoustic models, namely, subspace distribution clustering hidden Markov models and semi-continuous hidden Markov models. However, these models require also large memory to acquire high recognition accuracy. In this paper, we propose a new hybrid model using subspace distribution clustering hidden Markov model and semi-continuous hidden Markov model with the aim of achieving much more compact acoustic models.
Original language | English |
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Title of host publication | 8th International Conference on Spoken Language Processing, ICSLP 2004 |
Publisher | International Speech Communication Association |
Pages | 669-672 |
Number of pages | 4 |
Publication status | Published - 2004 |
Event | 8th International Conference on Spoken Language Processing, ICSLP 2004 - Jeju, Jeju Island, Korea, Republic of Duration: 2004 Oct 4 → 2004 Oct 8 |
Other
Other | 8th International Conference on Spoken Language Processing, ICSLP 2004 |
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Country/Territory | Korea, Republic of |
City | Jeju, Jeju Island |
Period | 04/10/4 → 04/10/8 |
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language