• Researchers develop real-time lyric gene

    From ScienceDaily@1:317/3 to All on Tue Aug 10 21:30:42 2021
    Researchers develop real-time lyric generation technology to inspire
    song writing

    Date:
    August 10, 2021
    Source:
    University of Waterloo
    Summary:
    Music artists can find inspiration and new creative directions
    for their song writing with technology.



    FULL STORY ========================================================================== Music artists can find inspiration and new creative directions for their
    song writing with technology developed by Waterloo researchers.


    ========================================================================== LyricJam, a real-time system that uses artificial intelligence (AI)
    to generate lyric lines for live instrumental music, was created by
    members of the University's Natural Language Processing Lab.

    The lab, led by Olga Vechtomova, a Waterloo Engineering professor cross- appointed in Computer Science, has been researching creative applications
    of AI for several years.

    The lab's initial work led to the creation of a system that learns
    musical expressions of artists and generates lyrics in their style.

    Recently, Vechtomova, along with Waterloo graduate students Gaurav Sahu
    and Dhruv Kumar, developed technology that relies on various aspects of
    music such as chord progressions, tempo and instrumentation to synthesize lyrics reflecting the mood and emotions expressed by live music.

    As a musician or a band plays instrumental music, the system continuously receives the raw audio clips, which the neural network processes to
    generate new lyric lines. The artists can then use the lines to compose
    their own song lyrics.



    ==========================================================================
    "The purpose of the system is not to write a song for the artist,"
    Vechtomova explains. "Instead, we want to help artists realize their
    own creativity. The system generates poetic lines with new metaphors
    and expressions, potentially leading the artists in creative directions
    that they haven't explored before." The neural network designed by the researchers learns what lyrical themes, words and stylistic devices are associated with different aspects of music captured in each audio clip.

    For example, the researchers observed that lyrics generated for ambient
    music are very different than those for upbeat music.

    The research team conducted a user study, inviting musicians to play
    live instruments while using the system.

    "One unexpected finding was that participants felt encouraged by the
    generated lines to improvise," Vechtomova said. "For example, the
    lines inspired artists to structure chords a bit differently and take
    their improvisation in a new direction than originally intended. Some
    musicians also used the lines to check if their improvisation had the
    desired emotional effect." Another finding from the study highlighted the co-creative aspect of the experience. Participants commented that they
    viewed the system as an uncritical jamming partner and felt encouraged
    to play their musical instruments even if they were not actively trying
    to write lyrics.

    Since LyricJam went live in June this year, over 1,500 users worldwide
    have tried it out.

    The team's research, to be presented at the International Conference on Computations Creativity this September, has been pre-published on arXiv.

    Musicians interested in trying out LyricJam can access it at https:// lyricjam.ai.

    ========================================================================== Story Source: Materials provided by University_of_Waterloo. Note:
    Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Olga Vechtomova, Gaurav Sahu, Dhruv Kumar. LyricJam: A system for
    generating lyrics for live instrumental music. Submitted to arXiv,
    2021 [abstract] ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2021/08/210810104709.htm

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