A robust and sensitive word boundary decision algorithm

A robust and sensitive word boundary decision algorithm for automatic speech recognition (ASR) system is proposed. The algorithm uses a time-frequency feature to improve both robustness and sensitivity. The time-frequency features are passed through a bank of moving average filters for temporary decision of word boundary in each band. The decision results of each band are then passed through a median filter for the final decision. The adoption of time-frequency feature improves the sensitivity, while the median filtering improves the robustness. Proposed algorithm uses an adaptive threshold based on the signal-to-noise ratio (SNR) in each band which further improves the decision performance. Experimental result shows that the proposed algorithm outperforms the Q.Li et al’s robust algorithm.