RESEARCH · RESEARCH · #2716
Paris Smaragdis joins MIT to advance machine listening research
Paris Smaragdis, a researcher with a background in computer music and machine learning, joined MIT in 2025 and leads work on machine listening — including sound-source separation, audio-aware devices, and tools for music analysis and synthesis. His group applies machine-learning approaches to enable machines to detect, separate, and interpret sounds in real-world environments.
KEY POINTS
- Paris Smaragdis, a researcher with a background in computer music and machine learning, joined MIT in 2025 and leads work on machine listening — including sound-source separation, audio-aware devices, and tools for music analysis and synthesis.
- His group applies machine-learning approaches to enable machines to detect, separate, and interpret sounds in real-world environments.
- Improving machine listening expands AI perception capabilities with applications in safety, industry monitoring, and music technology, enabling systems that can detect and interpret complex audio scenes.
WHY IT MATTERS
Improving machine listening expands AI perception capabilities with applications in safety, industry monitoring, and music technology, enabling systems that can detect and interpret complex audio scenes.