Name
Title | ||
|---|---|---|
Comparison of three approaches to phonetic string generation for large vocabulary speech recognition |
Abstract | ||
|---|---|---|
We are building a large vocabulary, isolated word preselection system according to a bottom-up design strategy. It will be used in the development of a dictation machine for Spanish and it is composed of three main modules: feature extraction, phonetic string build up and lexical access. In the second one, we are considering three different technological approaches based on static modeling (SM), Hidden Markov Models (HMM) and Neural Networks (NN). This paper will compare these three alternatives in terms of recognition performance, training complexity and computational load, and will conclude with the results of the comparison in order to adopt the most suitable approach depending on the task. |
Year | Venue | Keywords |
|---|---|---|
1994 | ICSLP | bottom up,hidden markov model,neural network,speech recognition,feature extraction |
Field | DocType | Citations |
Speech corpus,Vocabulary speech recognition,String generation,Pattern recognition,Computer science,Speech recognition,Phonetic search technology,Time delay neural network,Natural language processing,Artificial intelligence | Conference | 1 |
PageRank | References | Authors |
0.48 | 6 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Javier Macías Guarasa | 1 | 138 | 25.19 |
| Manuel A. Leandro | 2 | 6 | 2.35 |
| Xavier Menéndez-Pidal | 3 | 62 | 10.26 |
| José Colás | 4 | 100 | 14.98 |
| Ascension Gallardo | 5 | 1 | 0.81 |
| José Manuel Pardo | 6 | 152 | 30.36 |
| Santiago Aguilera | 7 | 32 | 5.65 |