- audio classification
- sound source separation
- automatic music transcription
- self localization and speaker tracking
- speech recognition
- speech synthesis
The following people at TUT are involved in INSPIRE projects:
TUT is the host for one INSPIRE project
- ENR-3: Modelling the perceptual grouping of sounds by sparse auditory signal representations. The human auditory system organizes mixtures of sounds into streams using grouping cues such as harmonicity and common modulations. This bottom-up processing contributes to the recognition of sounds in noise. The existing computational models of the phenomenon are very limited. The project will develop a computational model of primary grouping of sounds based on modern machine learning methods such as sparse coding and non-negative matrix factorization, which have been successfully used to stream complex mixtures sounds. The developed model provides a mid-level representation that can be used as a basis of higher-level models to predict speech intelligibility in environmental noises. The representation itself can be used to predict separability of different types of speech and noise.
TUT is also the second host of INSPIRE project ENR-2.