Recognizing reverberant speech with RASTA-PLP

By Brian Kingsbury, Nelson Morgan. 1997

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Citations in the corpus

Time-Frequency Masking in the Complex Domain for Speech Dereverberation and Denoising (2017, neutral): “Additionally, the performance of speech processing applications is degraded in reverberant environments, where reverberation causes automatic speech recognition (ASR) [22] and speaker identification systems [45] to”
Robust speech recognition using the modulation spectrogram (1998, methodology): “We have used both visualization and ASR experiments to develop these representations (Greenberg and Kingsbury, 1997; Kingsbury and Morgan, 1997; Kingsbury et al., 1997).”
Speech dereverberation and denoising using complex ratio masks (2017, background): “This presents challenges for many applications, such as, automatic speech recognition (ASR) [1], speaker identification [2], and hearing aid design.”
Transfer Learning from Audio-Visual Grounding to Speech Recognition (2019, background): “Such features can be hand-crafted by leveraging prior knowledge [11, 12, 13, 14], or they can be learned in a data-driven fashion.”
Learning Spectral Mapping for Speech Dereverberation and Denoising (2015, background): “degradation in automatic speech recognition (ASR) [17] and”
Tandem connectionist feature extraction for conventional HMM systems (2000, background): “One approach that has shown itself to be beneficial time and again in hybrid systems is feature stream combination via simple averaging of the log posterior probabilities from several independent acoustic model networks [4, 5].”