Speech Recognition and Understanding

Speech Recognition and Understanding Description

1 Recent Results on Hidden Markov Models.- Invited papers.- Hidden Markov Models for Speech Recognition Strengths and Limitations.- Hidden Markov Models and Speaker Adaptation.- A 20,000 word Automatic Speech Recognizer. Adaptation to French of the US TANGORA System.- Automatic Adjustments of the Markov Models Topology for Speech Recognition Applications over the Telephone.- Phonetic Structure Inference of Phonemic HMM.- Phonetic Units and Phonotactical Structure Inference by Ergodic Hidden Markov Models.- Clustering of Gaussian Densities in Hidden Markov Models.- Developments in High-Performance Connected Digit Recognition.- Robust Speaker-Independent Hidden Markov Model Based Word Spotter.- Robust Speech Recognition in Noisy and Reverberant Environments.- An ISDN Speech Server based on Speaker Independent Continuous Hidden Markov Models.- RAMSES: A Spanish Demisyllable Based Continuous Speech Recognition System.- Speaker Independent, 1000 Words Speech Recognition in Spanish.- Continuously Variable Transition Probability HMM for Speech Recognition.- 2 Continuous Speech Recognition Systems.- Invited papers.- Context-Dependent Phonetic Hidden Markov Models for Speaker-Independent Continuous Speech Recognition (Abstract).- Speaker-Independent Continuous Speech Recognition Using Continuous Density Hidden Markov Models.- Contributed papers.- A Fast Lexical Selection Strategy for Large Vocabulary Continuous Speech Recognition.- Performance of a Speaker-Independent Continuous Speech Recognizer.- Automatic Transformation of Speech Databases for Continuous Speech Recognition.- Iterative Optimization of the Data Driven Analysis in Continuous Speech.- Syllable-based Stochastic Models for Continuous Speech Recognition.- Word Hypothesization in Continuous Speech Recognition.-Phone Recognition Using High Order Phonotactic Constraints.- An Efficient Structure for Continuous Speech Recognition.- Search Organization for Large Vocabulary Continuous Speech Recognition.- 3 Connectionist Models of Speech.- Invited papers.- Neural Networks or Hidden Markov Models for Automatic Speech Recognition: Is there a Choice?.- Neural Networks for Continuous Speech Recognition.- Connectionist Large Vocabulary Speech Recognition.- The Cortical Column as a Model for Speech Recognition: Principles and First Experiments.- Contributed papers.- Radial Basis Functions for Speech Recognition.- Phonetic Features Extraction Using Time-Delay Neural Networks.- Improved Broad Phonetic Classification and Segmentation with an Auditory Model.- Automatic Learning of a Production Rule System for Acoustic-Phonetic Decoding.- 4 Stochastic Models for Language and Dialogue.- Invited papers.- Stochastic Grammars and Pattern Recognition.- Basic Methods of Probabilistic Context Free Grammars.- A Probabilistic Approach to Person-Robot Dialogue.- Contributed papers.- Experimenting Text Creation by Natural-Language, Large-Vocabulary Speech Recognition.- DUALGRAM: An Efficient Method for Representing Limited-Domain Language Models.- Strategies for Speech Recognition and Understanding Using Layered Protocols.- 5 Understanding and Dialogue Systems.- Invited papers.- TINA: A Probabilistic Syntactic Parser for Speech Understanding Systems.- The Voyager Speech Understanding System: A Progress Report.- The Interaction of Word Recognition and Linguistic Processing in Speech Understanding.- Linguistic Processing in a Speech Understanding System.- Contributed papers.- Linguistic Tools for Speech Recognition and Understanding.- Evidential Reasoning and the Combination of Knowledge and StatisticalTechniques in Syllable Based Speech Recognition.- 6 Speech Analysis, Coding and Segmentation.- Contributed papers.- Data Base Management for Use with Acoustic-Phonetic Speech Data Bases.- BPF Outputs Compared with Formant Frequencies and LPCs for the Recognition of Vowels.- A Codification of Error Signal by Splines Functions.- Specific Distance for Feature Selection in Speech Recognition.- Multiple Template Modeling of Sublexical Units.- Learning Structural Models of Sublexical Units.- On the Use of Negative Samples in the MGGI Methodology and its Application for Difficult Vocabulary Recognition Tasks.- A New Method for Dynamic Time Alignment of Speech Waveforms.- A New Technique for Automatic Segmentation of Continuous Speech.- Segmentation of Speech based upon a Linear Model of the Effects of Coarticulation 549 P.J. D.