An ARHMM-Based Speech Analysis Method and an Evaluation of a Singing-Voice Recognition

摘要

We have previously described an Auto-Regressive Hidden Markov Model (AR-HMM) and an accompanying parameter estimation method [5], [6]. The AR-HMM was obtained by combining an AR process with an HMM introduced as a non-stationary excitation model. We demonstrated that the AR-HMM can accurately estimate the characteristics of both articulatory systems and excitation signals from high-pitched speech. In this paper, we apply the AR-HMM to feature extraction from singing voices and evaluate the recognition accuracy of the AR-HMM-based approach.