What are the most promising areas for future research in generative AI for audio and speech?

1 Quality and realism

One of the main goals of generative AI for audio and speech is to produce high-quality and realistic outputs that can fool human listeners or match their expectations. This requires overcoming technical limitations such as noise, distortion, artifacts, and mismatched features. It also requires understanding and modeling the nuances and variations of natural sound and speech, such as emotions, accents, styles, and contexts. Future research in this area could focus on improving the data quality, the generative models, the evaluation metrics, and the user feedback mechanisms.

2 Diversity and representation

Another important goal of generative AI for audio and speech is to generate diverse and representative outputs that can capture the richness and variety of human sound and speech. This requires addressing issues such as data bias, underrepresentation, and oversimplification. It also requires developing methods that can generate novel and diverse sounds and voices that go beyond the existing data or mimic the creativity of human artists. Future research in this area could focus on enhancing the data diversity, the generative diversity, the ethical guidelines, and the social impact.

3 Ethics and responsibility

A related goal of generative AI for audio and speech is to ensure that the outputs are ethical and responsible, and that they do not harm or deceive human listeners or speakers. This requires tackling problems such as privacy, consent, authenticity, and accountability. It also requires educating and empowering the users and the public about the potential risks and benefits of generative AI for audio and speech, and how to use it responsibly and critically. Future research in this area could focus on strengthening the data protection, the output verification, the user awareness, and the regulatory frameworks.

4 Creativity and expression

A final goal of generative AI for audio and speech is to enable and enhance the creativity and expression of human users and creators. This requires bridging the gap between the technical and the artistic aspects of sound and speech generation, and finding ways to collaborate and co-create with human partners. It also requires exploring and expanding the possibilities and boundaries of generative AI for audio and speech, and creating new forms and genres of sound and speech art. Future research in this area could focus on fostering the user interaction, the output interpretation, the artistic innovation, and the cultural appreciation.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?