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.

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 of Waterloo'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 synthesise 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.

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.

We describe a real-time system that receives a live audio stream from a jam session and generates lyric lines that are congruent with the live music being played. Two novel approaches are proposed to align the learned latent spaces of audio and text representations that allow the system to generate novel lyric lines matching live instrumental music. One approach is based on adversarial alignment of latent representations of audio and lyrics, while the other approach learns to transfer the topology from the music latent space to the lyric latent space. A user study with music artists using the system showed that the system was useful not only in lyric composition, but also encouraged the artists to improvise and find new musical expressions. Another user study demonstrated that users preferred the lines generated using the proposed methods to the lines generated by a baseline model.

Artificial Intelligence is the notion of machines that exhibit intelligence and mimic cognitive functions that are usually associated with humans such as learning, reasoning, predicting, planning, recognising, and even problem-solving. Now, AI tools are being increasingly integrated into technological solutions and now it can even be induced in to generate lyrics that match the style of unique music artists. Now, the researchers at the University of Waterloo, Canada, have recently achieved this feat by developing a system that can generate such song lyrics. According to Olga Vechtomova, University of Waterloo, one of the minds behind this innovation presses on the fact that the base of the research is the ultimate result of curiosity that imbibes in each and every human being and that is to know whether a machine can generate lines that could sound like the lyrics of my favourite music artists. While working on text generative models, The research team founded that neural networks had the capability to generate some of the most creative and impressive lines of text.