T. H. Applebaum

Enhancing the discrimination of speaker independent hidden Markov models with corrective training

Brian Hanson, T. H. Applebaum, 1989, International Conference on Acoustics, Speech, and Signal Processing,.

Robust speaker-independent word recognition using static, dynamic and acceleration features: experiments with Lombard and noisy speech

Brian Hanson, T. H. Applebaum, B. Hanson, 1990, International Conference on Acoustics, Speech, and Signal Processing.

Regression features for recognition of speech in quiet and in noise

Brian Hanson, T. H. Applebaum, B. Hanson, 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

Stereopsis with large disparities: Discrimination and depth magnitude

T. H. Applebaum, J. M. Foley, W. Richards, 1975, Vision Research.

Tradeoffs in the design of regression features for word recognition

Ted H. Applebaum, Brian A. Hanson, T. H. Applebaum, 1991, EUROSPEECH.

Spectral Dynamics for Speech Recognition Under Adverse Conditions

Jean-Claude Junqua, Ted H. Applebaum, Brian Hanson, 1996 .

Subband or cepstral domain filtering for recognition of Lombard and channel-distorted speech

Ted H. Applebaum, Brian A. Hanson, T. H. Applebaum, 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Multistage word recognizer based on reliably detected phoneme similarity regions

T. H. Applebaum, Philippe Morin, 2000 .

Speech representation by feature-based word prototypes comprising phoneme targets having reliable high similarity

T. H. Applebaum, Philippe Morin, 1998 .

Time derivatives, cepstrai normaiization, and spectral parameter filtering for continuously spelled names over the telephone

Jean-François Mari, Jean-Claude Junqua, Dominique Fohr, 1995, EUROSPEECH.