Abstract
Speech technologies have been developed for decades as a typical signal processing area, while the last decade has brought a huge progress based on new machine learning paradigms. Owing not only to their intrinsic complexity but also to their relation with cognitive sciences, speech technologies are now viewed as a prime example of interdisciplinary knowledge area. This review article on speech signal analysis and processing, corresponding machine learning algorithms, and applied computational intelligence aims to give an insight into several fields, covering speech production and auditory perception, cognitive aspects of speech communication and language understanding, both speech recognition and text-to-speech synthesis in more details, and consequently the main directions in development of spoken dialogue systems. Additionally, the article discusses the concepts and recent advances in speech signal compression, coding, and transmission, including cognitive speech coding. To conclude, the main intention of this article is to highlight recent achievements and challenges based on new machine learning paradigms that, over the last decade, had an immense impact in the field of speech signal processing.
Highlights
According to Kuhn’s theory of scientific revolutions [1], the science makes progress through the revolutionary changes of prevailing scientific paradigms, where a paradigm represents a set of beliefs and values and technical and methodological procedures common to a scientific community
After a short retrospective of the main scientific paradigms based on the knowledge of speech production and auditory perception, this article presents new achievements and perspectives based on the new machine learning paradigm related to neuroscience and advanced signal processing
After a brief review of sound pressure waves and speech signal features, speech production and auditory perception including cognitive and linguistic points of view will be elaborated in more detail in the following subsections
Summary
Vlado Delic ,1 Zoran Peric ,2 Milan Secujski ,1 Niksa Jakovljevic ,1 Jelena Nikolic ,2 Dragisa Miskovic ,1 Nikola Simic ,2 Sinisa Suzic ,1 and Tijana Delic 1. Speech technologies have been developed for decades as a typical signal processing area, while the last decade has brought a huge progress based on new machine learning paradigms. Is review article on speech signal analysis and processing, corresponding machine learning algorithms, and applied computational intelligence aims to give an insight into several fields, covering speech production and auditory perception, cognitive aspects of speech communication and language understanding, both speech recognition and text-to-speech synthesis in more details, and the main directions in development of spoken dialogue systems. The main intention of this article is to highlight recent achievements and challenges based on new machine learning paradigms that, over the last decade, had an immense impact in the field of speech signal processing
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