Difference between revisions of "2017:Automatic Lyrics-to-Audio Alignment"
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The task of automatic lyrics-to-audio alignment has as an end goal the synchronization between an audio recording of singing and its corresponding written lyrics. The start and end timestamps of lyrics units can be estimated on different granularity: phonemes, words, lyrics lines, phrases. | The task of automatic lyrics-to-audio alignment has as an end goal the synchronization between an audio recording of singing and its corresponding written lyrics. The start and end timestamps of lyrics units can be estimated on different granularity: phonemes, words, lyrics lines, phrases. | ||
| − | For this task word-level granularity | + | For this task word-level alignment and sentence (lyrics lines) granularity are required. |
=== Task specific mailing list === | === Task specific mailing list === | ||
Revision as of 16:20, 31 May 2017
Contents
Description
The task of automatic lyrics-to-audio alignment has as an end goal the synchronization between an audio recording of singing and its corresponding written lyrics. The start and end timestamps of lyrics units can be estimated on different granularity: phonemes, words, lyrics lines, phrases. For this task word-level alignment and sentence (lyrics lines) granularity are required.
Task specific mailing list
Data
The evaluation dataset contains 11 songs of popular music with annotations of timestamps of the words and the sentences. The audio has two versions: the original with instrumental accompaniment and a cappella singing voice only one.
You can read in detail about how the dataset was made here: Recognition of Phonemes in A-cappella Recordings using Temporal Patterns and Mel Frequency Cepstral Coefficients. The dataset has been kindly provided by Jens Kofod Hansen.
