You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review 
Chapter Title:  Multi-Stage Algorithms 
1. Abstract of Cited Paper (BIB001):  A robust dereverberation method is presented for speech enhancement in a situation requiring adaptation where a speaker shifts his/her head under reverberant conditions causing the impulse responses to change frequently. We combine correlation-based blind deconvolution with modified spectral subtraction to improve the quality of inverse-filtered speech degraded by the estimation error of inverse filters obtained in practice. Our method computes inverse filters by using the correlation matrix between input signals that can be observed without measuring room impulse responses. Inverse filtering reduces early reflection, which has most of the power of the reverberation, and then, spectral subtraction suppresses the tail of the inverse-filtered reverberation. The performance of our method in adaptation is demonstrated by experiments using measured room impulse responses. The subjective results indicated that this method provides superior speech quality to each of the individual methods: blind deconvolution and spectral subtraction.

Literature Review:
During the last decade, several multi-stage algorithms were proposed for the enhancement of reverberant speech. In BIB001 , Nakatani and Miyoshi proposed a system capable of blind dereverberation of one microphone speech, by employing the harmonic structure of speech. In this system, a sinusoidal representation was used to approximate the direct sound in the reverberant environments and adaptive harmonic filters were first employed to estimate the voiced clean speech from the reverberant speech signal. This estimation was then used to derive a dereverberation filter. This method, however, requires accurate estimation of the fundamental frequency from the reverberant speech. Wu and Wang  proposed a two-stage model to enhance reverberant speech. In the first stage, an inverse filter of the room impulse response was estimated, to increase the SRR by maximizing the kurtosis of the LP residual. In the second stage, long term reverberation effects were removed using the spectral subtraction approach. In BIB002 , a hybrid dereverberation method was proposed, which combined correlation based blind deconvolution and modified spectral subtraction to suppress the tail of reverberation and improve the processed speech quality. Inverse filtering reduced the early reflection that constitutes most of the power of the reverberation. Then, the modified spectral subtraction suppressed the tail of the inverse-filtered speech.