Extraction of Vocal - Tract System
نویسندگان
چکیده
|We propose methods to track natural variations in the characteristics of the vocal-tract system from speech signals. We are especially interested in the cases where these characteristics vary over time, as happens in dynamic sounds such as consonant-vowel transitions. We show that the selection of appropriate analysis segments is crucial in these methods and we propose a selection based on estimated instants of signiicant excitation. These instants are obtained by a method based on the average group-delay property of minimum-phase signals. In voiced speech they correspond to the instants of glottal closure. The vocal-tract system is characterized by its formants parameters, which are extracted from the analysis segments. Because the segments are always at the same relative position in each pitch period, in voiced speech the extracted formants are consistent across successive pitch periods. We demonstrate the results of the analysis for several diicult cases of speech signals.
منابع مشابه
Algorithmic Surface Extraction from MRI Data - Modelling the Human Vocal Tract
A procedure for the vectorisation and feature extraction of the human vocal tract is proposed. The raw data is obtained by high resolution 3D MRI. Because the amount of manual work in the data processing has been minimised, large datasets can be treated. The vectorised data can be used for both numerical as well as physical modelling of the vocal tract biophysics, including speech and applicati...
متن کاملEffects of Voice Therapy on Vocal Tract Discomfort in Muscle Tension Dysphonia
Introduction: Patients with muscle tension dysphonia (MTD) suffer from several physical discomforts in their vocal tract. However, few studies have examined the effects of voice therapy (VT) on the vocal tract discomfort (VTD) in patients with voice disorders. Therefore, the aim of the present study was to investigate the effects of VT on the VTD in patients with MTD. Materi...
متن کاملImproving Performance of Speaker Identification System Using Complementary Information Fusion
Feature extraction plays an important role as a front-end processing block in speaker identification (SI) process. Most of the SI systems utilize like Mel-Frequency Cepstral Coefficients (MFCC), Perceptual Linear Prediction (PLP), Linear Predictive Cepstral Coefficients (LPCC), as a feature for representing speech signal. Their derivations are based on short term processing of speech signal and...
متن کاملComparison Between Different Methods for Epoch Extraction from Speech Signal
Speech is produced by exciting the vocal tract system by an excitation source. The excitation is significant at the instants of glottal closure. These instants of significant excitation are called Epochs. Epochs play a significant role in speech processing and is used are used in many applications. There are different methods for extraction of epochs from speech signal. In this paper we have di...
متن کاملExtraction of articulators in x-ray image sequences
We describe a method for tracking tongue, lips, and throat in X-ray films showing the side-view of the vocal tract. The technique uses specialized histogram normalization techniques and a new tracking method that is robust against occlusion, noise, and spontaneous, nonlinear deformations of articulators. The tracking results characterize the configuration of the vocal tract over time and can be...
متن کاملOn the time variability of vocal tract for speaker recognition
A novel scheme to analyze the effects of time variability of vocal tract for speaker recognition is proposed. We adopt a pitch synchronous feature extraction method to describe even more detailed characteristics of vocal tract, and decompose it into rapidly varying and slowly varying components with a specified linear filter along with time axis. Speaker identification tasks are performed with ...
متن کامل