Overview on speech processing: fundamentals, techniques and applications
19 Feb 2019, 15:00 — Genova
Speaker:
Zied Mnasri — DIBRIS
Zied Mnasri — DIBRIS
Abstract:
Nowadays applications are more and more interactive, which means that an optimal human-machine interaction is required. Then speech is an obvious and a natural way to achieve this goal. However, many challenges are still to be looked after, such as speech/speaker variability, noise and reverberation reduction, emotion recognition/synthesis...etc. Therefore, speech processing applications have been taking advantage from the development of many related fields, such as digital signal processing (DSP), computational linguistics, and more recently machine learning. In this talk, an introduction to speech processing will be presented, including a) fundamental aspects, such as speech signal modeling and representation, b) an overview of speech signal analysis methods, c) some well-known applications, like speech recognition and text-to-speech synthesis, and d) the current and future trends of speech processing using machine learning. Though this topic is too broad to be presented with more depth, the basic notions presented here could be deepened in every direction, to explore the techniques and the possibilities of speech communication.
Nowadays applications are more and more interactive, which means that an optimal human-machine interaction is required. Then speech is an obvious and a natural way to achieve this goal. However, many challenges are still to be looked after, such as speech/speaker variability, noise and reverberation reduction, emotion recognition/synthesis...etc. Therefore, speech processing applications have been taking advantage from the development of many related fields, such as digital signal processing (DSP), computational linguistics, and more recently machine learning. In this talk, an introduction to speech processing will be presented, including a) fundamental aspects, such as speech signal modeling and representation, b) an overview of speech signal analysis methods, c) some well-known applications, like speech recognition and text-to-speech synthesis, and d) the current and future trends of speech processing using machine learning. Though this topic is too broad to be presented with more depth, the basic notions presented here could be deepened in every direction, to explore the techniques and the possibilities of speech communication.
Bio:
Dr. Zied Mnasri obtained his PhD. in Feb. 2011 in electrical engineering. Since Sept. 2011, He has been working as assistant professor at University Tunis El Manar, Tunisia, teaching electronics, microcontrollers and digital signal processing. Since Sept. 2018, he's been a research fellow at DIBRIS, working with Prof. Francesco Masulli and Prof. Stefano Rovetta. His main research interests inlcude speech processing using machine learning.
Dr. Zied Mnasri obtained his PhD. in Feb. 2011 in electrical engineering. Since Sept. 2011, He has been working as assistant professor at University Tunis El Manar, Tunisia, teaching electronics, microcontrollers and digital signal processing. Since Sept. 2018, he's been a research fellow at DIBRIS, working with Prof. Francesco Masulli and Prof. Stefano Rovetta. His main research interests inlcude speech processing using machine learning.