Waveform-based speech recognition using hidden filter models: parameter selection and sensitivity to power normalization

No abstract is available for this paper.

• Publication year

  1994

• Venue

  IEEE Transactions on Speech and Audio Processing

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1109/89.260337
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A stochastic model of speech incorporating hierarchical nonstationarity

  1993cited by this paper
• Structural design of hidden Markov model speech recognizer using multivalued phonetic features: comparison with segmental speech units.

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

  1992cited by this paper
• On the application of mixture AR hidden Markov models to text independent speaker recognition

  1991cited by this paper
• Modeling microsegments of stop consonants in a hidden Markov model based word recognizer

  1990cited by this paper
• A linear predictive HMM for vector-valued observations with applications to speech recognition

  1990cited by this paper
• Continuously adaptive linear predictive coding of speech

  1988cited by this paper
• Hidden Markov models: a guided tour

  1988cited by this paper
• Mixture autoregressive hidden Markov models for speech signals

  1985cited by this paper
• Maximum likelihood estimation for multivariate observations of Markov sources

  1982cited by this paper
• Linear predictive hidden Markov models and the speech signal

  1982cited by this paper
• An improved endpoint detector for isolated word recognition

  1981cited by this paper
• An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process

  1972cited by this paper
• Calculation of Bayes' Recognition Error for Two Multivariate Gaussian Distributions

  1969cited by this paper
• On a measure of divergence between two statistical populations defined by their probability distributions

  1943cited by this paper

• WaDeNet: Wavelet Decomposition based CNN for Speech Processing

  2020cites this paper
• End-to-end acoustic modeling using convolutional neural networks for HMM-based automatic speech recognition

  2019cites this paper
• Speech Processing

  2018cites this paper
• Silent Communication Device

  2017cites this paper
• Towards End-to-End Speech Recognition

  2016cites this paper
• TROPE R HCRAESE R PAID I END-TO-END ACOUSTIC MODELING USING CONVOLUTIONAL NEURAL NETWORKS FOR AUTOMATIC SPEECH RECOGNITION

  2016cites this paper
• Deep Discriminative and Generative Models for Pattern Recognition

  2015cites this paper
• Summary and Future Directions.

  2015cites this paper
• Deep Generative and Discriminative Models for Speech Recognition

  2015cites this paper
• From Speech Recognition to Language and Multimodal Processing

  2015cites this paper
• A tutorial survey of architectures, algorithms, and applications for deep learning

  2014cites this paper
• Exploring Deep Learning Methods for Discovering Features in Speech Signals

  2014cites this paper
• Deep Learning: Methods and Applications

  2014cites this paper
• PAID I ESTIMATING PHONEME CLASS CONDITIONAL PROBABILITIES FROM RAW SPEECH SIGNAL USING CONVOLUTIONAL NEURAL NETWORKS

  2013cites this paper
• Speech Recognition Front End Without Information Loss

  2013influential citation
• Data Mining Approach for Deceptive Phishing Detection System

  2013cites this paper
• Estimating phoneme class conditional probabilities from raw speech signal using convolutional neural networks

  2013cites this paper
• Phoneme Classification in High-Dimensional Linear Feature Domains

  2013influential citation
• Deep Learning for Signal and Information Processing

  2013cites this paper
• Recent advances in deep learning for speech research at Microsoft

  2013cites this paper
• Acoustic Analysis for Automatic Speech Recognition

  2013cites this paper
• Deceptive phishing detection system: From audio and text messages in Instant Messengers using Data Mining approach

  2012cites this paper
• RECONSTRUCTED STATE SPACE MODEL FOR RECOGNITION OF CONSONANT - VOWEL (CV) UTTERANCES USING SUPPORT VECTOR MACHINES

  2012cites this paper
• Time–domain non-linear feature parameter for consonant classification

  2012cites this paper
• Three Classes of Deep Learning Architectures and Their Applications: A Tutorial Survey

  2012cites this paper
• State Space Point Distribution Parameter for Support Vector Machine Based CV Unit Classification

  2012cites this paper
• Deep Convex Net: A Scalable Architecture for Speech Pattern Classification

  2011cites this paper
• State Space Point Distribution Parameter for Support Vector Machine Based Cv Unit Classification

  2011cites this paper
• An Overview of Deep-Structured Learning for Information Processing

  2011cites this paper
• Combined waveform-cepstral representation for robust speech recognition

  2011cites this paper
• Front-End, Back-End, and Hybrid Techniques for Noise-Robust Speech Recognition

  2011cites this paper
• Word recognition from speech signal using Spectrum Analysis and LPC

  2011cites this paper
• Phoneme Classification in Linear Feature Domains

  2010cites this paper
• Spectral Enhancement Methods

  2009cites this paper
• A convex optimization method for joint mean and variance parameter estimation of large-margin CDHMM

  2008cites this paper
• A novel low complexity speech recognition approach

  2008cites this paper
• Single- and multi-microphone speech dereverberation using spectral enhancement

  2007cites this paper
• HMM-Based Gain Modeling for Enhancement of Speech in Noise

  2007cites this paper
• Structured speech modeling

  2006influential citation
• Dynamic Speech Models: Theory, Algorithms, and Applications

  2006cites this paper
• Hidden Markov models with states depending on observations

  2005cites this paper
• Speech enhancement using a switching Kalman filter with a perceptual post-filter

  2005cites this paper
• Relaxed statistical model for speech enhancement and a priori SNR estimation

  2005cites this paper
• Relaxed Statistical Model for Speech Enhancement

  2005cites this paper
• Time-domain isolated phoneme classification using reconstructed phase spaces

  2005cites this paper
• A study on IMM with NPHMM and an application to speech enhancement

  2004cites this paper
• Adaptive model-based speech enhancement

  2001cites this paper
• Recognition of noisy speech by a nonstationary AR HMM with gain adaptation under unknown noise

  2001cites this paper
• Speech enhancement based on IMM with NPHMM

  2001cites this paper
• Mixture IMM for speech enhancement under nonstationary noise

  2000cites this paper
• Time-domain approach using multiple Kalman filters and EM algorithm to speech enhancement with nonstationary noise

  2000cites this paper
• On the applications of the interacting multiple model algorithm for enhancing noisy speech

  2000influential citation
• An Acoustical Study of Syllables of Mandarin Speech

  1999cites this paper
• Speech enhancement based on neural predictive hidden Markov model

  1998cites this paper
• Speech analysis and recognition using interval statistics generated from a composite auditory model

  1998cites this paper
• HMM-based strategies for enhancement of speech signals embedded in nonstationary noise

  1998cites this paper
• HMM-based speech recognition using state-dependent, discriminatively derived transforms on mel-warped DFT features

  1997cites this paper
• Speech recognition using autosegmental representation of phonological units with interface to the trended HMM

  1997cites this paper
• Production models as a structural basis for automatic speech recognition

  1997cites this paper
• Efficient recursive estimation for speech enhancement in colored noise

  1996influential citation
• Recursive speech enhancement using the EM algorithm with initial conditions trained by HMM's

  1996cites this paper
• Comparative performance of spectral subtraction and HMM-based speech enhancement strategies with application to hearing and design

  1994cites this paper
• COMPARATIVE PERFORMANCE OF SPECTRAL SUBTRACTION WITH APPLICATION TO HEARING AID DESIGN AND HMM-BASED SPEECH ENHANCEMENT STRATEGIES

  1994cites this paper
• A stochastic model of speech incorporating hierarchical nonstationarity

  1993cites this paper
• A __ -_ B Speech Elsevier Production Models as a Structural Basis for Automatic Speech Recognition

  year unknowncites this paper