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2018
Conference Paper
Title
Retrieval of Song Lyrics from Sung Queries
Abstract
Retrieving the lyrics of a sung recording from a database of text documents is a research topic that has not received much attention so far. Such a retrieval system has many practical applications, e.g. for karaoke applications or for indexing large song databases by their lyric content. We present a new method for lyrics retrieval. An acoustic model trained on singing is used to obtain phoneme probabilities from sung queries, which are then mapped to phoneme sequences. These are compared against lines of textual lyrics in a large corpus in order to retrieve the best-matching song. The approach is tested on three sung datasets. Lyrics are retrieved from a set of 300 possible songs (12,000 lines of lyrics). The results are highly encouraging and could be used further to perform automatic lyrics alignment and keyword spotting for large databases of songs, or for retrieving lyrics from the internet.
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