Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation

The tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the latter can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.

Dynamics of the North American continent

The forces that cause deformation of western North America have been debated for decades. Recent studies, primarily based on analysis of crustal stresses in the western United States, have suggested that the deformation of the region is mainly controlled by gravitational potential energy (GPE) variations and boundary loads, with basal tractions due to mantle flow playing a relatively minor role. We address these issues by modelling the deviatoric stress field over western North America from a 3-D finite element mantle circulation model with lateral viscosity variations. Our approach takes into account the contribution from both topography and shallow lithosphere structure (GPE) as well as that from deeper mantle flow in one single model, as opposed to separate lithosphere and circulation models, as has been done so far. In addition to predicting the deviatoric stresses we also jointly fit the constraints of geoid, dynamic topography and plate motion both globally and over North America, in order to ensure that the forces that arise in our models are dynamically consistent. We examine the sensitivity of the dynamic models to different lateral viscosity variations. We find that circulation models that include upper mantle slabs yield a better fit to observed plate velocities. Our results indicate that a model of GPE variations coupled with mantle convection gives the best fit to the observational constraints. We argue that although GPE variations control a large part of the deformation of the western United States, deeper mantle tractions also play a significant role. The average deviatoric stress magnitudes in the western United States range 30-40 MPa. The cratonic region exhibits higher coupling to mantle flow than the rest of the continent. We find that a relatively strong San Andreas fault gives a better fit to the observational constraints, especially that of plate velocity in western North America.