Joseph Di Martino

Universidade de São Paulo — Brazil

Computer Science · Physical Sciences

7h-index261citations57works0.52yr avg
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Research Topics

Speech Recognition and Synthesis(31), Speech and Audio Processing(27), Music and Audio Processing(8), Natural Language Processing Techniques(7), Voice and Speech Disorders(7)

Publications57 total

Global Framework for Scientific Event: A 32-Country and 118-Expert Collaborative Effort
Barw Medical Journal·2024Open Access
Assessment of Self-Supervised Denoising Methods for Esophageal Speech Enhancement
Applied Sciences·2024· 1 citedOpen Access
Any-to-One Non-Parallel Voice Conversion System Using an Autoregressive Conversion Model and LPCNet Vocoder
Preprints.org·2023Open Access
Any-to-One Non-Parallel Voice Conversion System Using an Autoregressive Conversion Model and LPCNet Vocoder
Applied Sciences·2023· 6 citedOpen Access
Any-to-One Non-Parallel Voice Conversion System Using an Autoregressive Conversion Model and LPCNet Vocoder
Preprints.org·2023· 1 citedOpen Access
Intelligibility Improvement of Esophageal Speech Using Sequence-to-Sequence Voice Conversion with Auditory Attention
Applied Sciences·2022· 4 citedOpen Access
Non-Parallel Voice Conversion System Using An Auto-Regressive Model
2022· 4 cited
Denoising Esophageal Speech using Combination of Complex and Discrete Wavelet Transform with Wiener filter and Time Dilated Fourier Cepstra
ITM Web of Conferences·2022· 3 citedOpen Access
Rehaussement de la parole œsophagienne par une technique de conversion de voix fondée sur l'estimation de multiples réseaux de neurones profonds et de fonctions de conversion spectrale
HAL (Le Centre pour la Communication Scientifique Directe)·2021Open Access
Une nouvelle méthodologie prédictive fondée sur un modèle séquence à séquence utilisé pour la transformation de la parole œsophagienne en voix laryngée
HAL (Le Centre pour la Communication Scientifique Directe)·2021Open Access
A novel voice conversion approach using cascaded powerful cepstrum predictors with excitation and phase extracted from the target training space encoded as a KD-tree
International Journal of Speech Technology·2019· 1 cited
Enhancement of esophageal speech obtained by a voice conversion technique using time dilated Fourier cepstra
International Journal of Speech Technology·2018· 10 cited
Improving the computational performance of standard GMM-based voice conversion systems used in real-time applications
2018· 2 cited
Enhancement of esophageal speech using statistical and neuromimetic voice conversion techniques
HAL (Le Centre pour la Communication Scientifique Directe)·2018· 2 cited
Real Time Context-Independent Phone Recognition Using a Simplified Statistical Training Algorithm
2016· 1 citedOpen Access
Prediction of Cepstral Excitation Pulses for Voice Conversion
2016· 1 citedOpen Access
A corroborative study on improving pitch determination by time–frequency cepstrum decomposition using wavelets
SpringerPlus·2016· 3 citedOpen Access
A preliminary study on improving the recognition of esophageal speech using a hybrid system based on statistical voice conversion
SpringerPlus·2015· 6 citedOpen Access
An architectural comparison of signal reconstruction algorithms from short-time Fourier transform magnitude spectra
International Journal of Speech Technology·2015· 2 cited
New Results - Statistical Modeling of Speech
2015
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Frequent Co-authors

Fadoua Bahja(8), Yves Laprié(7), El Hassan Ibn Elhaj(7), Kadria Ezzine(6), Jean‐Paul Haton(6), Dominique Fohr(6), Imen Ben Othmane(5), Mondher Frikha(5), Kamel Smaı̈li(5), Vincent Colotte(5), Kaïs Ouni(4), Driss Aboutajdine(4), Mouhcine Chami(4), Irina Illina(4), Anne Bonneau(4), Slim Ouni(4), Othman Lachhab(3), Ahmed Hammouch(3), El Hassane Ibn Elhaj(3), Antoine Christophe(3)