Enhancing Speech In Noisy Environment: A Review

Abstract

Speech signal is the primary mode of communication amongst humans. It is also used for the communication between human and machine, i.e., human-machine interaction (IoTs), communication with a range of electronic devices, e.g., Internet of Things (IoTs), and even with virtual assistants (VAs) or online search engines, e.g., Google etc. The use of speech signals for the communication over mobile phones, and smart phones based virtual assistants such as Cortana, Siri, Alexa etc. is well known. Usually, this communication involves some communication medium, which is susceptible to noise. The speech or audio signal used for the communication may be adversely affected by the noise that is added unwantedly over the communication channel or medium. It not only degrades the quality of communication and intelligibility of the message or content, but also leads to poor experience. The quality of speech signal may be degraded significantly, due to changes in the characteristics of speech signal, during the process from transmission to reception and the signal conversions involved at both ends. Hence there is a need for algorithms, signal processing methods, acoustic features and classifiers etc. for noise detection and noise reduction during the speech signal communication process. In this paper, a comprehensive review of various speech signal databases, speech signal processing methods used, acoustic features extracted and the classifiers used in different studies is presented. A comprehensive and comparative view of results obtained in different studies, and the applications is also presented. This study should be helpful to all the researchers working in the domains of speech signal processing in noisy environments or degraded speech etc.