A dynamic, feature-based approach to the interface between phonology and phonetics for speech modeling and recognition

By Li Deng. 1998

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Citations in the corpus

Deep Learning: Methods and Applications (2014, background): “It is important to note that the unique elasticity of temporal dynamics of speech as elaborated in [45, 73, 76, 83] would require temporally”
Dynamic Speech Models: Theory, Algorithms, and Applications (2006, methodology): “One parametric form of the hidden trajectory constructed to satisfy both these constraints is the critically damped exponential function of time [33,114].”
A path-stack algorithm for optimizing dynamic regimes in a statistical hidden dynamic model of speech (2000, unknown): “This is a special version of the general statistical hidden dynamic model described in Deng (1999) and Deng (1998).”
An Overview of Deep-Structured Learning for Information Processing (2011, background): “Subsequent work added a new hidden layer into the dynamic model so as to explicitly account for the target-directed, articulatory-like properties in human speech generation (Deng and Ramsay, 1997; Deng, 1998; Bridle et al., 1998; Deng, 1999; Picone et al., 1999; Deng, 2003).”
Efficient decoding strategies for conversational speech recognition using a constrained nonlinear state-space model (2003, background): “…speech have been known for sometime (e.g., [2], [4], [7], [8], etc.), so are the limitations of some more recent approaches based on the stochastic segment models (SSM) [3], [9], [10], [14], [19], [20], [26], [27], [33] that have largely ignored correlations across pronunciation units.”
Structured speech modeling (2006, methodology): “One parametric form of the hidden trajectory constructed to satisfy both of these constraints is the following explicit temporal function of time : (5) as proposed and analyzed in [15].”
Continuous latent variable models for dimensionality reduction and sequential data reconstruction (2001, background): “Deng et al. (1997) mention a good, well-known example: stop epenthesis after nasals.”
Switching Dynamic System Models for Speech Articulation and Acoustics (2004, unknown): “The approaches outlined in [31, 12, 11, 14, 13] have emphasized the functional signi cance of abstract, \task" dynamics in speech production and recognition.”