JOURNAL ARTICLE

High-speed speaker adaptation using phoneme dependent tree-structured speaker clustering

Abstract

The tree-structured speaker clustering was proposed as a highspeed speaker adaptation method. It can select the model which is most similar to a target speaker. However, this method does not consider speaker difference dependent on phoneme class. In this paper, we propose a speaker adaptation method based on speaker clustering by taking speaker difference dependent on phoneme class into account. The experimental results showed that the new method gave a better performance than the original method. Furthermore, we propose the improved method which use a tree-structure of a similar phoneme as the substitute for the phoneme which does not appear in the adaptation data. From the experimental results, the improved method gave a better performance than the method previously proposed.

Keywords:
Computer science Speaker diarisation Cluster analysis Speech recognition Speaker recognition Adaptation (eye) Tree (set theory) Class (philosophy) Pattern recognition (psychology) Artificial intelligence Mathematics

Metrics

1
Cited By
0.42
FWCI (Field Weighted Citation Impact)
2
Refs
0.67
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing

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