Allows user to visualize and track tonal patterns in real time for MIDI files. Pitches map to positions in the Spiral Array model, and durations to the radii of the spheres. Each collection of notes also generates a center of effect (c.e.), and the distance of the c.e. to each key. The software was implemented using Java2 SDK, with 3D API.

This research supports IMSC's research in user centered sciences through the modeling of music perception in the context of North Indian Classical Music (NICM).

The proposed research involves development of methods for content-based indexing of music databases using a combination of signal processing and knowledge-based methods, design of statistical algorithms for enabling queries using sung or hummed melodies, and design of robust search techniques for retrieving the queried information especially in the presence of uncertainty.

Unsupervised speaker indexing sequentially detects points where a speaker identity changes in a multi-speaker audio stream, and categorizes each speaker segment, without any prior knowledge about the speakers.

Speech recognition is an essential component of any human computer interaction (HCI) scheme, which aspires to be natural.

Speech recognition is an essential component of any Human Computer Interaction (HCI) scheme, which aspires to be natural. Thus, high accuracy speech recognition is of critical importance in making natural man-machine interfaces.

Emotions (anger, happiness, sadness, etc.) are inseparable components of the natural human speech. Because of that, the level of human speech can only be achieved with the ability to synthesize emotions.

Spoken language adds naturalness and efficiency to human-machine interactions with both children and adults.

One of the goals of this project is to develop methods for compressing speech signals for a distributed speech recognition task.

This research aims at investigating several feature sets such as acoustic, lexical, and discourse features, and classification algorithms for classifying spoken utterances based on the emotional state of the speaker.