Stochastic trajectory modeling and sentence searching for continuous speech recognition

No abstract is available for this paper.

• Publication year

  1997

• Venue

  IEEE Transactions on Speech and Audio Processing

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1109/89.554267
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Issues in acoustic modeling of speech for automatic speech recognition

  1994cited by this paper
• Statistical trajectory models for phonetic recognition

  1994cited by this paper
• Speech recognition using hidden Markov models with polynomial regression functions as nonstationary states

  1994cited by this paper
• Segmental phoneme recognition using piecewise linear regression

  1994cited by this paper
• Stochastic trajectory modeling for speech recognition

  1994cited by this paper
• State-dependent time warping in the trended hidden Markov model

  1994cited by this paper
• Nonlinear time alignment in stochastic trajectory models for speech recognition

  1994cited by this paper
• Use of temporal correlation between successive frames in a hidden Markov model based speech recognizer

  1993cited by this paper
• Modeling and search in continuous speech recognition

  1993influential reference
• Phoneme HMMs constrained by frame correlations

  1993cited by this paper
• ML estimation of a stochastic linear system with the EM algorithm and its application to speech recognition

  1993cited by this paper
• Hidden Markov models with templates as non-stationary states: an application to speech recognition

  1993influential reference
• Iterative transformation and alignment for speech labeling

  1993cited by this paper
• DTW-based phonetic labeling using explicit phoneme duration constraints

  1992cited by this paper
• A generalized hidden Markov model with state-conditioned trend functions of time for the speech signal

  1992cited by this paper
• Modeling acoustic transitions in speech by state-interpolation hidden Markov models

  1992cited by this paper
• Fast algorithms for phone classification and recognition using segment-based models

  1992cited by this paper
• A real-time recurrent error propagation network word recognition system

  1992cited by this paper
• VINICS: a continuous speech recognizer based on a new robust formulation

  1991cited by this paper
• Signal-to-String Conversion Based on High Likelihood Regions Using Embedded Dynamic Programming

  1991cited by this paper
• Continuous speech recognition based on high plausibility regions

  1991cited by this paper
• Development of an acoustic-phonetic hidden Markov model for continuous speech recognition

  1991cited by this paper
• A tutorial on hidden Markov models and selected applications in speech recognition

  1989cited by this paper
• A stochastic segment model for phoneme-based continuous speech recognition

  1989influential reference
• Mathematical foundations of hidden Markov models

  1988cited by this paper
• Large-vocabulary speaker-independent continuous speech recognition: the sphinx system

  1988cited by this paper
• Explicit time correlation in hidden Markov models for speech recognition

  1987cited by this paper
• The acoustic-modeling problem in automatic speech recognition

  1987cited by this paper
• A stochastic segment model for phoneme-based continuous speech recognition

  1987influential reference
• Continuously variable duration hidden Markov models for automatic speech recognition

  1986cited by this paper
• Speaker-independent isolated word recognition using dynamic features of speech spectrum

  1986cited by this paper
• Lessons in digital estimation theory

  1986cited by this paper
• Mixture autoregressive hidden Markov models for speaker independent isolated word recognition

  1986cited by this paper
• Explicit modelling of state occupancy in hidden Markov models for automatic speech recognition

  1985cited by this paper
• An Algorithm for Vector Quantizer Design

  1980cited by this paper
• Dynamic programming, the viterbi algorithm, and low cost speech recognition

  1978cited by this paper
• An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process

  1972cited by this paper
• Recursive bayesian estimation using gaussian sums

  1971cited by this paper

• Summary and Future Work

  2022cites this paper
• Phoneme Boundary Analysis using Multiway Geometric Properties of Waveform Trajectories

  2020cites this paper
• Efficient Continuous Speech Recognition Approaches for Dravidian Languages

  2020cites this paper
• Automatic continuous speech recogniser for Dravidian languages using the auto associative neural network

  2016cites this paper
• Phone classification via manifold learning based dimensionality reduction algorithms

  2016cites this paper
• A New Speaker Recognition System with Combined Feature Extraction Techniques in Continuous Speech

  2015cites this paper
• Compensating for speaker or lexical variabilities in speech for emotion recognition

  2014cites this paper
• Towards better performance with heterogeneous training data in acoustic modeling using deep neural networks

  2014cites this paper
• Speech Recognition Technology: A Survey on

  2013cites this paper
• Nonlinear compensation and heterogeneous data modeling for robust speech recognition

  2013cites this paper
• Exploiting sparsity in stranded hidden Markov models for automatic speech recognition

  2012cites this paper
• Exploring Discriminative Speech Trajectory Structures

  2012cites this paper
• Stranded Gaussian mixture hidden Markov models for robust speech recognition

  2012cites this paper
• Improved hidden Markov model for speech recognition and POS tagging

  2012cites this paper
• Smoothing speech trajectories by regularization

  2012cites this paper
• Speech Recognition by Machine, A Review

  2010cites this paper
• A Review on Speech Recognition Technique

  2010cites this paper
• Babble Noise: Modeling, Analysis, and Applications

  2009cites this paper
• Fast and robust stochastic segment model for Mandarin digital string recognition

  2008cites this paper
• A Knowledge based Approach Using Fuzzy Inference Rules for Vowel Recognition

  2008cites this paper
• Probabilistic latent speaker analysis for large vocabulary speech recognition

  2007cites this paper
• Trajectory Clustering for Solving the Trajectory Folding Problem in Automatic Speech Recognition

  2007cites this paper
• Advances in phone-based modeling for automatic accent classification

  2006influential citation
• An integrated approach to the detection and classification of accents/dialects for a spoken document retrieval system

  2005cites this paper
• SpeechFind: advances in spoken document retrieval for a National Gallery of the Spoken Word

  2005cites this paper
• Use of trajectory models for automatic accent classification

  2003influential citation
• Toward robust parametric trajectory segmental model for vowel recognition

  2002cites this paper
• Tree-structured maximum a posteriori adaptation for a segment-based speech recognition system

  2002cites this paper
• Experiments on distant-talking speech recognition in meeting room using extended MAM

  2002cites this paper
• Stochastic trajectory model analysis for accent classification

  2002cites this paper
• SPEECH RECOGNITION USING NEURAL NETWORKS

  2001cites this paper
• Structural Maximum a Posteriori Adaptation for Mixture Stochastic Trajectory Framework

  2001cites this paper
• Word Recognition for Tractor Control

  2001cites this paper
• On adaptive decision rules and decision parameter adaptation for automatic speech recognition

  2000cites this paper
• An improved maximum model distance approach for HMM-based speech recognition systems

  2000cites this paper
• Final Report of Cost Action 249 Continuous Speech Recognition over the Telephone Country Acronym Name of Institution

  2000cites this paper
• Hybrid neural predictor/stochastic trajectory models for Chinese speech recognition

  1999cites this paper
• An experimental study of speaker verification sensitivity to computer voice-altered imposters

  1999cites this paper
• Trainable Speech Synthesis Based On Trajectory Modeling Of Line Spectrum Pair Frequencies

  1998cites this paper
• Environment normalization training and environment adaptation using mixture stochastic trajectory model

  1998cites this paper
• Towards A Compact Speech Recognizer: Subspace Distribution ClusteringHidden Markov Model

  1998cites this paper
• Assessing the importance of the segmentation probability in segment-based speech recognition

  1998cites this paper
• SPEECH RECOGNITION USING NEURAL NETWORKS

  1998cites this paper
• Speaker normalization training for mixture stochastic trajectory model

  1997cites this paper
• The importance of segmentation probability in segment based speech recognizers

  1997cites this paper
• Elimination of trajectory folding phenomenon: HMM, trajectory mixture HMM and mixture stochastic trajectory model

  1997cites this paper