An overview of Automatic Speech Recognition Preprocessing Techniques

Speech signal preprocessing is the first and the most important step in the automatic speech recognition process. The preprocessing of speech consists of cleaning the speech signal from ambient and undesirable noises, detecting speech activity, and normalizing the length of the vocal tract. The objective of preprocessing a speech signal is to make the speech recognition systems computationally more efficient through the application of several preprocessing techniques, such as speech pre-emphasis, vocal tract length normalization, voice activity detection, noise removal, framing, and windowing. This paper gives an overview of the fundamentals of speech signal preprocessing techniques, by highlighting the specifics and the requirements of each technique. We also explore all aspects that can improve the results of each technique. We aim that the content of this paper will help researchers improve the quality of their speech recognition systems by identifying appropriate speech preprocessing techniques to use in their experimental settings.