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Retrieving Tract Variables From Acoustics: A Comparison of Different Machine Learning Strategies
2010
IEEE Journal on Selected Topics in Signal Processing
Many different studies have claimed that articulatory information can be used to improve the performance of automatic speech recognition systems. Unfortunately, such articulatory information is not readily available in typical speaker-listener situations. Consequently, such information has to be estimated from the acoustic signal in a process which is usually termed "speech-inversion." This study aims to propose and compare various machine learning strategies for speech inversion: Trajectory
doi:10.1109/jstsp.2010.2076013
pmid:23326297
pmcid:PMC3544523
fatcat:ahhhv3juojc6hpke2zmxhnxg5m