Influence of Vector Quantization on Isolated Word Recognition
| Tipo de publicação: | Inproceedings |
| Citação: | font94:eusip |
| Booktitle: | European Signal Processing Conference (EUSIPCO 94), Edinburgh, UK |
| Ano: | 1994 |
| Páginas: | 115-118 |
| URL: | http://diuf.unifr.ch/people/he... |
| Resumo: | Vector Quantization can be considered as a data compression technique. In the last few years, vector quantization has been increasingly applied to reduce problem complexity like pattern recognition. In speech recognition, discrete systems are developed to build up real-time systems. This paper presents original results by comparing the K-Means and the Kohonen approaches on the same recognition platform. Influence of some quantization parameters is also investigated. It can be observed through the results presented in this paper that the quantization quality has a significant influence on the recognition rates. Surprisingly, the Kohonen approach leads to better recognition results despite its poor distortion performance. |
| Palavras-chave: | Kohonen, Speech Recognition, Vector Quantization |
| Autores | |
| Adicionado por: | [] |
| Total mark: | 0 |
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