Robust Continuous Speech Recognition Technology Program Summary
نویسندگان
چکیده
The major objective of this program is to develop and demonstrate robust, high-performance continuous speech recognition (CSR) techniques and systems focused on applications in spoken language systems (SLS). A key supporting objective is to develop techniques for integration of CSR and natural language processing (NLP) systems in SLS applications. The CSR techniques are based on a continuousobservation hidden Markov model (HMM) approach, using tied Ganssian mixtures to model the speech parameters. A stack-decoder control structure is being developed and utilized, both for efficient largevocabulary recognition, and to facilitate integration of CSR and NLP systems.
منابع مشابه
An Information-Theoretic Discussion of Convolutional Bottleneck Features for Robust Speech Recognition
Convolutional Neural Networks (CNNs) have been shown their performance in speech recognition systems for extracting features, and also acoustic modeling. In addition, CNNs have been used for robust speech recognition and competitive results have been reported. Convolutive Bottleneck Network (CBN) is a kind of CNNs which has a bottleneck layer among its fully connected layers. The bottleneck fea...
متن کاملRobust Speech Recognition
The Lincoln Laboratory Program in Robust Speech Recognition Technology was initiated in FY85 with the major goal of developing techniques for high-performance speech recognition under the stress and noise conditions typical of the fighter cockpit. After achieving significant advances in robust isolated-word recognition (IWR) during FY85 and FY86, the program evolved in FY87 to the development o...
متن کاملRobust Speech Recognition Technology Program Summary
The major objective of this program is to develop and demonstrate robust, high-performance continuous speech recognizer (CSR) techniques and systems focused on application in spoken language systems (SLS). A key supporting objective is to develop techniques for integration of CSR and natural language processing (NLP) systems in SLS applications. The CSR techniques are based on a continuous-obse...
متن کاملRobust Continuous Speech Recognition
The pnrnary objective of this basic research program is to develop robust methods and models for speaker-independent acoustic recognition of spontaneously-produced, :ontinuous speech. The work has focussed on developing accurate and detailed models of phonemes and their coarticulation for the purpose of large-vocabulary continuous speech recognition. Important goals of this work are to achieve ...
متن کاملImproving the performance of MFCC for Persian robust speech recognition
The Mel Frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. In this paper to achieve a satisfactorily performance in Automatic Speech Recognition (ASR) applications we introduce a noise robust new set of MFCC vector estimated through following steps. First, spectral mean normalization is a pre-processing which applies to t...
متن کامل