Temporal variation of tonal spectrum of tambura

Tambura is an essential drone accompaniment used in Indian music concerts. It acts as an immediate reference of pitch for both the artists and listeners. The four strings of Tambura are tuned to the frequency ratio :1:1: . Careful listening to Tambura sound reveals that the tonal spectrum is not stationary but is time varying. The object of this study is to make a detailed spectrum analysis to find out the nature of temporal variation of the tonal spectrum of Tambura sound. Results of the analysis are correlated with perceptual evaluation conducted in a controlled acoustic environment. A significant result of this study is to demonstrate the presence of several notes which are normally not noticed even by a professional artist. The effect of bridge in Tambura in producing the so called “live tone” is explained through time and frequency parameters of Tambura sounds.

Experimental Investigation on the Effect of Advanced Bus-Clamping Pulsewidth Modulation on Motor Acoustic Noise

Voltage source inverters (VSIs) supply nonsinusoidal voltages to induction motor drives, leading to line current distortion and torque pulsation. Conventional space vector pulsewidth modulation (PWM) techniques are widely used in VSIs on the account of good waveform quality and high dc bus utilization. In a conventional space vector PWM technique, the switching sequence begins with one zero state and ends with the other zero state in a subcycle. Some novel switching sequences have been proposed, which employ only one zero state but apply one of the two active states twice in a subcycle. One pair of such special switching sequences has recently been shown to reduce the pulsating torque considerably. In this paper, the conventional and special switching sequences are compared experimentally in terms of acoustic noise. In the low-and medium-speed ranges, the special switching sequence is seen to reduce the amplitude of the tonal component of noise at the switching frequency considerably and is also found to result in spread spectrum.

Compressive sensing for music signals: comparison of transforms with coherent dictionaries

Compressive Sensing (CS) is a new sensing paradigm which permits sampling of a signal at its intrinsic information rate which could be much lower than Nyquist rate, while guaranteeing good quality reconstruction for signals sparse in a linear transform domain. We explore the application of CS formulation to music signals. Since music signals comprise of both tonal and transient nature, we examine several transforms such as discrete cosine transform (DCT), discrete wavelet transform (DWT), Fourier basis and also non-orthogonal warped transforms to explore the effectiveness of CS theory and the reconstruction algorithms. We show that for a given sparsity level, DCT, overcomplete, and warped Fourier dictionaries result in better reconstruction, and warped Fourier dictionary gives perceptually better reconstruction. “MUSHRA” test results show that a moderate quality reconstruction is possible with about half the Nyquist sampling.