Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 65 for “"Spectrogram"”.
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Spectrogram Track Detection: An Active Contour Algorithm
… domain by representing the time-series data as a spectrogram, in which slowly varying periodic signals appear as curvilinear tracks. The research is initiated with a survey of the literature, which is focused upon research into the detection of tracks within spectrograms. An investigation into …
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State-space multitaper spectrogram algorithms : theory and applications
I present the state-space multitaper approach for analyzing non-stationary time series. Nonstationary time series are commonly divided into small time windows for analysis, but existing methods lose predictive power by analyzing each window independently, even though nearby windows have similar …
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Formalizing knowledge used in spectrogram reading : acoustic and perceptual evidence from stops
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1988.
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PASSIVE RADAR TRACK CLUSTERING: HIGHER FIDELITY OF TARGET IDENTIFICATION AND CLASSIFICATION OF UNLABELED TRACKS
… preprocessed datasets: Raw Magnitude, Full Spectrogram, and Max Hold Spectrogram. We implemented SSL pipelines using K–Means and Gaussian Mixture Models (GMMs) to generate pseudo-labels from limited labeled data for classifier training. The Max Hold Spectrogram performs the best for both SL …
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AudioCNN: Audio Event Classification With Deep Learning Based Multi-Channel Fusion Networks
… by combining various audio features, including Spectrogram (SG), Chromagram (CG), and Mel Frequency Cepstral Coefficient (MFCC), for useful environmental sound classification. We propose the AudioCNN model based on a fusion network consisting of multiple Convolutional Neural Networks (CNN) with …
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Toward an interpretive framework of two-dimensional speech-signal processing
… such as the short-time Fourier transform and spectrogram. Speech-signal models of such representations have had utility in a variety of applications such as speech analysis, recognition, and synthesis. Nonetheless, they do not capture spectral, temporal, and joint spectrotemporal energy …
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Parts-based models and local features for automatic speech recognition
… (T-F) "patches" which act as filters over a spectrogram. The model structure encodes the patches' relative T-F positions. The second variation, referred to as a "speech schematic" model, more directly encodes the information in a spectrogram by using simple edge detectors and focusing more on …
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SIGNAL MODELS, ANALYSIS ALGORITHMS, AND SOFTWARE TOOLS FOR MODAL AUDIO RESYNTHESIS
… modal parameters by finding trajectories in the spectrogram of the input audio. However, SAMPLE encounters challenges with specific sounds, like acoustic beats, where two close frequencies interact and create a beating effect. To overcome this limitation, the thesis introduces BeatsDROP, an …
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Wavelet analysis of ULF magnetospheric waves
… data and is compared to the traditional spectrogram technique, in particular, with respect to structured Pc 1--2 emissions. This results in the conclusion that the frequency modulation evident in Pearl pulsations is not continuous, but is comprised of waves localized in both time and …
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Machine Learning for Radio Frequency Interference Flagging
… This is done through the use of time/frequency spectrogram data, relating to radio astronomy measurements, using the magnitudes and phases of each available polarization. Predictions for unseen test data are compared between algorithms, different implementations of those algorithms and each …
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Precise intensity and phase characterisation of optical telecommunication signals
… the phase profiles of these signals is based on spectrograms, and various developments and extensions of this method are presented. Finally, data modulated pulses in a 40 Gbit/s system are characterised before and after propagation in an installed fibre link, and excellent agreement is found …
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Time-Frequency Analysis and Filtering based on the Short-Time Fourier Transform
… the squared magnitude of the STFT known as the spectrogram – include signal denoising, instantaneous frequency estimation, and speech recognition.<br/>In this thesis, we first address the main limitation of the trade-off between time and frequency resolution for the TF analysis by proposing a …
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Safety and data quality of EEG recorded simultaneously with multi-band fMRI
… and cardioballistic artifacts along with a clean spectrogram. The heating induced by the MB sequence was lower than that of the SB sequence by a factor of 0.73 ± 0.38. This is consistent with an expected heating ratio of 0.64, calculated from the square of the ratio of B_(1+RMS) values of the …
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Whistler Waves Detection - Investigation of modern machine learning techniques to detect and characterise whistler waves
… of image classification and localisation on the spectrogram data generated by the VLF receivers to identify and localise each whistler. The data at hand has around 2300 events identified by AWD at SANAE and Marion and will be used as training, validation, and testing data. Three detector designs …
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Applications and Extensions of Quadratic Signal Representations
… representation to be consistent with a set of spectrogram-based energy measurements. The desired representation is obtained as the solution to a constrained-optimization problem. The optimization problem can be solved using a gradient-projection technique. The consistent TFR demonstrates …
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Acoustic-based machine learning diagnostic tool for voice disorders
… convolutional neural network (CNN) model with spectrogram of the speech as input, transfer learning from image recognition applications to pathological voice detection field using timefrequency representation as input, and a novel CNN model using data augmentation idea with scalogram of the …
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Improving Impulse Audio Source Separation using Generative Adversarial Networks for Phase Generation
… that Time-Frequency masking of the noisy signal spectrogram was the best candidate audio separation method for dynamic soundscapes such as tactical fields and music. We followed with an experimental investigation of the role of phase in Time-Frequency masking, finding its importance to the …
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Edge Device Speaker Verification
… to a microcontroller, we re-produce a log-mel spectrogram framework implemented in Python to our target device supported language: C++. We show that it is possible to build a reasonably accurate,EER ≤11%, generalizable text-independent speaker verification model which will fit on even the …
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End-to-end non-negative auto-encoders: a deep neural alternative to non-negative audio modeling
… NMF allows us to factorize the magnitude spectrogram to learn representative spectral bases that can be used for a wide range of applications. With the recent advances in deep learning, neural networks (NNs) have surpassed NMF in terms of performance. However, these NNs are trained …
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Unsupervised learning to quantify differences in song learning of experimental zebra finch populations
… to obvious abnormalities appearing in the song spectrogram. Overall, these results provide interesting ideas about isolate song learning, and act as a proof of concept for the use of sparse convolutional learning to compare bird populations.
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