Improvement of rejection performance of keyword spotting using anti-keywords derived from large vocabulary considering acoustical similarity to keywords

SUMMARYThis paper proposes a robust and fast lyric search method for music information retrieval (MIR). The effectiveness of lyric search systems based on full-text retrieval engines or web search engines is highly compromised when the queries of lyric phrases contain incorrect parts due to mishearing. To improve the robustness of the system, the authors introduce acoustic distance, which is computed based on a confusion matrix of an automatic speech recognition experiment, into Dynamic-Programming (DP)-based phonetic string matching to identify the songs that the misheard lyric phrases refer to. An evaluation experiment verified that the search accuracy is increased by 4.4% compared with the conventional method. Furthermore, in this paper a two-pass search algorithm is proposed to realize real-time execution. The algorithm pre-selects the probable candidates using a rapid index-based search in the first pass and executes a DP-based search process with an adaptive termination strategy in the second pass. Experimental results show that the proposed search method reduced processing time by more than 86.2% compared with the conventional methods for the same search accuracy.

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Improvement of rejection performance of keyword spotting using anti-keywords derived from large vocabulary considering acoustical similarity to keywords

Cited by 3 publications

References 5 publications

Robust and Fast Two-Pass Search Method for Lyric Search Covering Erroneous Queries Due to Mishearing

Robust and Fast Two-Pass Search Method for Lyric Search Covering Erroneous Queries Due to Mishearing

Application of speech analytics in information space monitoring systems

Robust and Fast Phonetic String Matching Method for Lyric Searching Based on Acoustic Distance

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