Name
Abstract | ||
|---|---|---|
The OpenKWS14 keyword search evaluation is one of the most challenging and influential evaluations in the field of speech recognition. Its goal is to build a high-performance keyword search system for a minority language with limited training data in a short period of time. We present the system of the Department of Electronic Engineering, Tsinghua University (THUEE team) for the OpenKWS14 keyword search evaluation. The highlights of the system include the use of convolutional maxout neural networks for acoustic modeling and the use of neural network language models for one-pass lattice generation. The final system is a fusion of 8 subsystems. The system has achieved an actual term weighted value (ATWV) of 0.5107 for the full language pack (FullLP) condition in the evaluation, ranking third among the participating teams. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) | Acoustic Modeling, Language Modeling, Deep Neural Network, Keyword Spotting, Low-Resource |
Field | DocType | ISSN |
Training set,Ranking,Computer science,Keyword search,Minority language,Neural network language models,Time delay neural network,Artificial intelligence,Deep learning,Artificial neural network,Machine learning | Conference | 1520-6149 |
Citations | PageRank | References |
3 | 0.39 | 18 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meng Cai | 1 | 68 | 8.24 |
| Zhiqiang Lv | 2 | 26 | 11.28 |
| Beili Song | 3 | 3 | 0.39 |
| Yongzhe Shi | 4 | 47 | 5.09 |
| Wei-lan Wu | 5 | 3 | 0.39 |
| Cheng Lu | 6 | 4 | 1.42 |
| Wei-Qiang Zhang | 7 | 136 | 31.22 |
| Jia Liu | 8 | 183 | 32.42 |