A Hidden Conditional Random Field-Based Approach for Thai Tone Classification

Authors

  • Natthawut Kertkeidkachorn Chulalongkorn University
  • Proadpran Punyabukkana Chulalongkorn University
  • Atiwong Suchato Chulalongkorn University

DOI:

https://doi.org/10.4186/ej.2014.18.3.99

Keywords:

Thai tone classification, Hidden Conditional Random Fields, Tone feature, Frequency scaling, Normalization technique and Fundamental frequency.

Abstract

In Thai, tonal information is a crucial component for identifying the lexical meaning of a word. Consequently, Thai tone classification can obviously improve performance of Thai speech recognition system. In this article, we therefore reported our study of Thai tone classification. Based on our investigation, most of Thai tone classification studies relied on statistical machine learning approaches, especially the Artificial Neural Network (ANN)-based approach and the Hidden Markov Model (HMM)-based approach. Although both approaches gave reasonable performances, they had some limitations due to their mathematical models. We therefore introduced a novel approach for Thai tone classification using a Hidden Conditional Random Field (HCRF)-based approach. In our study, we also investigated tone configurations involving tone features, frequency scaling and normalization techniques in order to fine tune performances of Thai tone classification. Experiments were conducted in both isolated word scenario and continuous speech scenario. Results showed that the HCRF-based approach with the feature F_dF_aF, ERB-rate scaling and a z-score normalization technique yielded the highest performance and outperformed a baseline using the ANN-based approach, which had been reported as the best for the Thai tone classification, in both scenarios. The best performance of HCRF-based approach provided the error rate reduction of 10.58% and 12.02% for isolated word scenario and continuous speech scenario respectively when comparing with the best result of baselines.

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Author Biographies

Natthawut Kertkeidkachorn

Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Proadpran Punyabukkana

Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Atiwong Suchato

Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Published

Vol 18 No 3, Jul 10, 2014

How to Cite

[1]
N. Kertkeidkachorn, P. Punyabukkana, and A. Suchato, “A Hidden Conditional Random Field-Based Approach for Thai Tone Classification”, Eng. J., vol. 18, no. 3, pp. 99-122, Jul. 2014.