Sound waves cause small vibrations in nearby objects. A few techniques exist in the literature that can extract sound from video. In this paper we study local vibration patterns at different image locations. We show that different locations in the image vibrate differently. We carefully aggregate local vibrations and produce a sound quality that improves state-of-the-art. We show that local vib...

Formant Dynamics is an interesting research field in Speech Perception, Speech Parameterizacion, Synthesis, and Recognition. The Spectrogram shown in Fig. 1.a, corresponding to the utterance “I wished you were here a year ago” reveals important dynamic changes in the positions of the poles in the Transfer Function of the Vocal Tract with time. In the associated template shown in Fig. 1.b, the s...

We experimentally demonstrate that an interferometric spectrogram (i.e., fringe- and frequency-resolved autocorrelation trace) with high signal-to-noise ratio can be processed by three different procedures to accurately retrieve the spectral phase profile. We also show that the data redundancy built in the interferometric spectrogram permits simultaneous retrieval of multiple spectral phase sol...

Abstract— For audio denoising, diagonal thresholding estimators of spectrogram coefficients produce a “musical noise” that degrades audio perception. We introduce a block thresholding which produces hardly any musical noise and improves the SNR compared to diagonal thresholdings or Ephraim and Malah estimators. Spectrogram coefficients are grouped into blocks to compute attenuation factors. Thi...

In this paper, we propose the method of heart rate (HR) and heart rate variability (HRV) spectrogram estimation by analyzing extracted hemoglobin concentration from facial color images. Our method does not require any special camera. In addition, stable presumption is possible even under the ambient light sources. As a result, we could get HR around 99% accuracy and could get HRV spectrogram wi...

Bistable perception emerges when a stimulus under continuous view is perceived as the alternation of two mutually exclusive states. Such a stimulus provides a unique opportunity for understanding the neural basis of visual perception because it dissociates the perception from the visual input. In this paper we analyze the dynamic activity of local field potential (LFP), simultaneously collected...

This project relies on computer vision techniques to build a practical music retrieval system. Our approach tackles traditional music identification as a corrupted sub-image retrieval problem from the 2-D spectrogram representation of the original songs. More specifically, a query snippet spectrogram is matched against our database using its descriptor representation. We utilize a novel pairwis...

In this paper, we propose Speaker Identification using two transforms, namely Haar Transform and Kekre’s Transform. The speech signal spoken by a particular speaker is converted into a spectrogram by using 25% and 50% overlap between consecutive sample vectors. The two transforms are applied on the spectrogram. The row mean of the transformed matrix forms the feature vector, which is used in th...

The short-time Fourier transform (STFT) based spectrogram is commonly used to analyze the time-frequency content of a signal. Depending on window size, the STFT provides a trade-off between time and frequency resolutions. This paper presents a novel method that achieves high resolution simultaneously in both time and frequency. We extend Probabilistic Latent Component Analysis (PLCA) to jointly...

We propose a probabilistic factorial sparse coder model for single channel source separation in the magnitude spectrogram domain. The mixture spectrogram is assumed to be the sum of the sources, which are assumed to be generated frame-wise as the output of sparse coders plus noise. For dictionary training we use an algorithm which can be described as non-negative matrix factorization with l spa...