Review of neural networks for speech recognition
Neural Computation
Cepstral parameter compensation for HMM recognition in noise
Speech Communication - Special issue on speech processing in adverse conditions
Large vocabulary speech recognition using subword units
Speech Communication - Speech science and technology: a selection from the papers presented at the Fourth International Conference in Speech Science and Technology (SST-92)
Statistical methods for speech recognition
Statistical methods for speech recognition
Improved modeling and efficiency for automatic transcription of Broadcast News
Speech Communication - Special issue on automatic transcription of broadcast news data
Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
Hidden Markov Models for Speech Recognition
Hidden Markov Models for Speech Recognition
Broadcast News Transcription Using HTK
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Tree-based state tying for high accuracy acoustic modelling
HLT '94 Proceedings of the workshop on Human Language Technology
A one pass decoder design for large vocabulary recognition
HLT '94 Proceedings of the workshop on Human Language Technology
Algorithms for an optimal A* search and linearizing the search in the stack decoder
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
Modeling durations of syllables using neural networks
Computer Speech and Language
Improved modeling of OOV words in spontaneous speech
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Temporal patterns (TRAPs) in ASR of noisy speech
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Dynamic programming search techniques for across-word modelling in speech recognition
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Buried Markov models for speech recognition
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
The application of hidden Markov models in speech recognition
Foundations and Trends in Signal Processing
Hybrid wavelet based LPC features for Hindi speech recognition
International Journal of Information and Communication Technology
Fast sequential decoding algorithm using a stack
IBM Journal of Research and Development
Robust adaptation to non-native accents in automatic speech recognition
Robust adaptation to non-native accents in automatic speech recognition
A study on the generalization capability of acoustic models for robust speech recognition
IEEE Transactions on Audio, Speech, and Language Processing
New uses for the N-best sentence hypotheses within the BYBLOS speech recognition system
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Subphonetic modeling with Markov states: senone
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
The general use of tying in phoneme-based HMM speech recognisers
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Front end analysis of speech recognition: a review
International Journal of Speech Technology
Filterbank optimization for robust ASR using GA and PSO
International Journal of Speech Technology
Integration of multiple acoustic and language models for improved Hindi speech recognition system
International Journal of Speech Technology
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In automatic speech recognition (ASR) systems, the speech signal is captured and parameterized at front end and evaluated at back end using the statistical framework of hidden Markov model (HMM). The performance of these systems depend critically on both the type of models used and the methods adopted for signal analysis. Researchers have proposed a variety of modifications and extensions for HMM based acoustic models to overcome their limitations. In this review, we summarize most of the research work related to HMM-ASR which has been carried out during the last three decades. We present all these approaches under three categories, namely conventional methods, refinements and advancements of HMM. The review is presented in two parts (papers): (i) An overview of conventional methods for acoustic phonetic modeling, (ii) Refinements and advancements of acoustic models. Part I explores the architecture and working of the standard HMM with its limitations. It also covers different modeling units, language models and decoders. Part II presents a review on the advances and refinements of the conventional HMM techniques along with the current challenges and performance issues related to ASR.