Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Anirban Patranabis is active.

Publication


Featured researches published by Anirban Patranabis.


CMMR'11 Proceedings of the 8th international conference on Speech, Sound and Music Processing: embracing research in India | 2011

On tanpura drone and brain electrical correlates

Matthias Braeunig; Ranjan Sengupta; Anirban Patranabis

We describe a new conceptual framework of using tanpura drone for auditory stimulation in EEG. The question of reference for baseline EEG in the resting condition where the subject has no task to perform is addressed. In a laboratory setting we observed spontaneous brain electrical activity during Tanpura drone stimulation and periods of silence. The sound stimulus was given by an electronic substitute Tanpura (EST) that allows to closely control its parameters. The timbral characteristics of the drone samples are given. The brain-electrical response of the subject is analyzed with global descriptors, a way to monitor the course of activation in the time domain in a three-dimensional state space, revealing patterns of global dynamical states of the brain. Preliminary results are presented that serve as a stepping stone for a larger longitudinal study.


Archive | 2017

Production, Perception and Cognition

Asoke Kumar Datta; Sandeep Singh Solanki; Ranjan Sengupta; Soubhik Chakraborty; Kartik Mahto; Anirban Patranabis

This chapter is devoted to muse over the basic principles behind the making of music instead of presenting a synopsis of techniques and technologies used in modern day music production. In the introductory chapter we attempted a comprehensive definition of music. Let us add further that music as an acoustical emotive (except for the emotion of anger, disgust) communication, generally universal in nature. The simultaneity of the three elements acoustics, emotion, and universality (not in the absolute sense) is integral to the definition.


Archive | 2017

Automatic Musical Instrument Recognition

Asoke Kumar Datta; Sandeep Singh Solanki; Ranjan Sengupta; Soubhik Chakraborty; Kartik Mahto; Anirban Patranabis

This chapter deals with analysis of musical instruments especially the Indian musical instruments by analyzing its sound. Sections 9.1, 9.2 and 9.3 concerns the automatic recognition of musical instruments with the idea that extract the perceptually relevant features from acoustic musical signals that a computer system “listen” to musical sounds and recognize which instrument is playing. For this, timbre of the sound of those musical instruments needs to be studied extensively. Only five musical instruments which are popularly adopted in Hindustani music were chosen for study.


Archive | 2017

Vadi-Samvadi Controversy and Statistics

Asoke Kumar Datta; Sandeep Singh Solanki; Ranjan Sengupta; Soubhik Chakraborty; Kartik Mahto; Anirban Patranabis

There is a concept of alankar in Indian music, meaning a musical ornament. The shastras talk about shabdalankars and varnalankars. The varnas include sthayi (stay on a note), arohi (ascent), awarohi (descent) and sanchari (mixture of ascent and descent). The rising and falling transitions can be further classified into convex, concave and linear. We also have hats and valleys. A hat may be interpreted as an ascent followed by immediate descent, and a valley as a descent followed by immediate ascent. By making a count of all the above, we can study the transitory as well as non-transitory pitch movements between the notes.


Archive | 2017

Tonic Detection and Shruti Analysis from Raga Performance

Asoke Kumar Datta; Sandeep Singh Solanki; Ranjan Sengupta; Soubhik Chakraborty; Kartik Mahto; Anirban Patranabis

The technological advances of modern times make it possible to have an in-depth analysis of songs of renowned singers of North Indian Classical music to objectively assess the vexing questions related to shrutis and swaras. Not only this, the issues related to musical scales in India are many, and to say the least, not simple.


Archive | 2017

Pitch Transition and Pitch Stability

Asoke Kumar Datta; Sandeep Singh Solanki; Ranjan Sengupta; Soubhik Chakraborty; Kartik Mahto; Anirban Patranabis

The pitch is the fundamental parameter for understanding objectively various aspect of melodic music. A pitch contour describes a series of relative pitch transitions adjoining the abstractions of a sequence of steady states called notes. While the quasi stationary states in the dynamics of pitch in Indian music have been elaborately discussed in other chapters it is also necessary to pay attention to the transitory movements.


Archive | 2017

Scales and Shruti Concept

Asoke Kumar Datta; Sandeep Singh Solanki; Ranjan Sengupta; Soubhik Chakraborty; Kartik Mahto; Anirban Patranabis

Music of modern days transcended the simplicity of early human music and its practical needs. The artistic and the aesthetic aspects began to emerge through its entertainment potential during the medieval times. Its beauty and serenity along with its potential to touch the emotional chord evoked intense interest among the earliest thinkers in every civilization and India is no exception. The recorded evidence of musical activities in India dates back to more than 2000 years.


Archive | 2017

Music Information Retrieval

Asoke Kumar Datta; Sandeep Singh Solanki; Ranjan Sengupta; Soubhik Chakraborty; Kartik Mahto; Anirban Patranabis

Music is a very interesting topic in our society as almost everyone enjoys listening to it and many wants to create. Broadly speaking, the research in Music Information Retrieval (MIR) is one of the upcoming research interest with the extraction and inference of meaningful features from music (from the audio signal), indexing of music using these features, and the development of deferent search and retrieval schemes (for instance, content-based search, music recommendation systems, or user interfaces for browsing large music collections), as defined by Downie (2003).


Physica A-statistical Mechanics and Its Applications | 2016

Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals

Archi Banerjee; Shankha Sanyal; Anirban Patranabis; Kaushik Banerjee; Tarit Guhathakurta; Ranjan Sengupta; Dipak Ghosh; Partha Ghose


Physica A-statistical Mechanics and Its Applications | 2016

A study on Improvisation in a Musical performance using Multifractal Detrended Cross Correlation Analysis

Shankha Sanyal; Archi Banerjee; Anirban Patranabis; Kaushik Banerjee; Ranjan Sengupta; Dipak Ghosh

Collaboration


Dive into the Anirban Patranabis's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Kartik Mahto

Birla Institute of Technology

View shared research outputs
Top Co-Authors

Avatar

Sandeep Singh Solanki

Birla Institute of Technology

View shared research outputs
Top Co-Authors

Avatar

Soubhik Chakraborty

Birla Institute of Technology

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge