From knowledge-ignorant to knowledge-rich modeling : a new speech research parading for next generation automatic speech recognition

By C. Lee. 2004

109 citations recorded by the source corpus.

How researchers see this paper

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An Overview of Deep-Structured Learning for Information Processing (2011, methodology): “We will describe this discriminative deep architecture in detail in Section V. Finally, the learning architecture developed for bottom-up, detection-based speech recognition proposed in (Lee, 2004) and developed since then can also be categorized in this discriminative deep architecture category.”
Machine Learning Paradigms for Speech Recognition: An Overview (2013, unknown): “Examples include deep-structured CRF, tandem-MLP architecture [94], [258], deep convex or stacking network [248] and its tensor version [242], [243], [259], and detection-based ASR architecture [235], [236], [260].”
Dynamic Speech Models: Theory, Algorithms, and Applications (2006, background): “, [3, 10, 11, 13, 20, 22, 32–39]) believe that the severe limitations of the HMM should be overcome and novel approaches to representing key aspects of the human speech process are highly desirable or necessary.”
Structured speech modeling (2006, unknown): “, [3], [6], [9], [29], [34], [40], [42], [49], [53], [59]).”