scholarly journals Acoustic-to-articulatory inversion by analysis-by-synthesis using cepstral coefficients

2013 ◽  
Vol 133 (5) ◽  
pp. 3248-3248
Author(s):  
Julie Busset ◽  
Yves Laprie
Keyword(s):  
Analysis By Synthesis ◽  
Cepstral Coefficients ◽  
Articulatory Inversion

Sequence-to-Sequence Articulatory Inversion Through Time Convolution of Sub-Band Frequency Signals

2020 ◽  
Author(s):  
Abdolreza Sabzi Shahrebabaki ◽  
Sabato Marco Siniscalchi ◽  
Giampiero Salvi ◽  
Torbjørn Svendsen
Keyword(s):  
Band Frequency ◽  
Articulatory Inversion

An analysis-by-synthesis study of Mandarin speech prosody

2016 ◽  
Author(s):  
Na Zhi ◽  
Daniel Hirst ◽  
Pier Marco Bertinetto ◽  
Aijun Li ◽  
Yuan Jia
Keyword(s):  
Speech Prosody ◽  
Analysis By Synthesis

scholarly journals Modelling of Amplitude Modulated Vocal Fry Glottal Area Waveforms Using an Analysis-by-Synthesis Approach

2021 ◽  
Vol 11 (5) ◽  
pp. 1990
Author(s):  
Vinod Devaraj ◽  
Philipp Aichinger
Keyword(s):  
Voice Quality ◽  
Low Frequency ◽  
Voice Disorder ◽  
Support Vector ◽  
Svm Classifier ◽  
Power Spectral ◽  
Analysis By Synthesis ◽  
Simple Support ◽  
Frequency Modulations ◽  
Synthesis Approach

The characterization of voice quality is important for the diagnosis of a voice disorder. Vocal fry is a voice quality which is traditionally characterized by a low frequency and a long closed phase of the glottis. However, we also observed amplitude modulated vocal fry glottal area waveforms (GAWs) without long closed phases (positive group) which we modelled using an analysis-by-synthesis approach. Natural and synthetic GAWs are modelled. The negative group consists of euphonic, i.e., normophonic GAWs. The analysis-by-synthesis approach fits two modelled GAWs for each of the input GAW. One modelled GAW is modulated to replicate the amplitude and frequency modulations of the input GAW and the other modelled GAW is unmodulated. The modelling errors of the two modelled GAWs are determined to classify the GAWs into the positive and the negative groups using a simple support vector machine (SVM) classifier with a linear kernel. The modelling errors of all vocal fry GAWs obtained using the modulating model are smaller than the modelling errors obtained using the unmodulated model. Using the two modelling errors as predictors for classification, no false positives or false negatives are obtained. To further distinguish the subtypes of amplitude modulated vocal fry GAWs, the entropy of the modulator’s power spectral density and the modulator-to-carrier frequency ratio are obtained.

scholarly journals Analysis-by-Synthesis Quantization for Compressed Sensing Measurements

2013 ◽  
Vol 61 (22) ◽  
pp. 5789-5800 ◽  
Author(s):  
Amirpasha Shirazinia ◽  
Saikat Chatterjee ◽  
Mikael Skoglund
Keyword(s):  
Compressed Sensing ◽  
Analysis By Synthesis
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