Improving Query-by-Singing/Humming by Combining Melody and Lyric Information

This paper proposes a novel method for improving query-by-singing/humming systems by using both melody and lyric information. First, singing/humming discrimination is performed to distinguish between singing and humming queries, which is achieved by considering the similarity between acoustic models. For the humming queries, a pitch-only melody recognition method that was ranked first among the MIREX (Music Information Retrieval Evaluation eXchange) query-by-singing/humming task submissions is applied. For the singing queries, a lyric similarity is computed using speech recognition techniques; the computed similarity is subsequently combined with the melody distance to exploit additional information in the lyrics. Several methods for combining melody distance and lyric similarity are investigated. Under the optimal experimental settings, the proposed query-by-singing/humming system achieves 51.19% error rate reduction for the top-10 retrieved results, indicating the feasibility of the proposed method.