robust speech recognition systems
Stereo-based histogram equalization for robust speech recognition
... ASR systems in noisy environments. Speech enhancement methods can be classified into two main categories ...approach, robust signal processing is employed to reduce the sensitivity of the ...
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Robust Speech Recognition for German and Dialectal Broadcast Programmes
... of speech and their corresponding text ...Usually speech recognition systems perform very well in conditions similar to the training ...these systems typically ...the speech ...
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Automatic Speaker Recognition System in Adverse Conditions — Implication of Noise and Reverberation on System Performance
... Abstract—Speaker recognition has been developed and evolved over the past few decades into a supposedly mature ...utilize robust features extracted from clean ...of recognition becomes crucial, ...
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Multi-candidate missing data imputation for robust speech recognition
... MDT systems involve much more intensive computation in the backend, as explained in Section ...competitive recognition accuracy, but also possesses the same efficiency as a conventional large vocabulary ...
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A Comparative Study of Histogram Equalization (HEQ) for Robust Speech Recognition
... of speech features but also their ...of speech features, some researchers have extended the principal idea of CMN and CMVN to the normalization of the third [Suk et ...of speech features [Hsu and Lee ...
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Exploiting correlogram structure for robust speech recognition with multiple speech sources
... the speech fragment decoding system (after Barker et ...to speech models is then used to search for the most likely combination of fragment labelling and speech model ...ceiving speech signals ...
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Features and Model Adaptation Techniques for Robust Speech Recognition: A Review
... noisy speech |Y(k)| 2 , hence the estimated clean spectrum will be ...degrades speech recognition ...enhancing speech for hearing, spectral subtraction has also been used to preprocess noisy ...
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Enhancing the magnitude spectrum of speech features for robust speech recognition
... of speech recognition ...pre-trained recognition model parameters so that the modified recognition models can more effectively clas- sify the mismatched test speech features collected in ...
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IMAGE DUPLICATION AND ROTATION DETECTION METHODS FOR STORAGE UTILIZATION
... Speech recognition systems have been recently used in wide varieties of real applications especially after the enormous technological revolution where smart phone and other gadgets within the reach ...
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Robust In-Car Speech Recognition Based on Nonlinear Multiple Regressions
... regression-based recognition systems described above, each driving condition was assumed to be known as a prior information and the regression parameters were trained within each driving ...car ...
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Robust recognition of strongly distorted speech
... The second architecture is based on ”modern” artificial neural networks and a com- pletely new field of deep learning has been created since their popularization. These discriminative hierarchical models have surpassed ...
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A Posterior Union Model with Applications to Robust Speech and Speaker Recognition
... speaker recognition systems need to be robust against unknown partial corruption of the acoustic features, where some of the feature components may be corrupted by noise, but knowledge about the ...
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Noise Robust Speech Recognition Applied to Voice-Driven Wheelchair
... In a voice-driven wheelchair, headset microphones should be placed as close to the wheelchair user’s mouth as possible to overcome the background noise. However, such microphones can be both dangerous and inconvenient ...
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Rethinking Speech Recognition on Mobile Devices
... on speech applications in developing regions, such as those for information access [8, 13] or those information management [9] have explored the use of ASR under three different models: embedded speech ...
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Robust Speech Recognition Using Factorial HMMs for Home Environments
... a speech-recognition function because their interface should be sufficiently easy for children and elderly people to ...current speech-recognition systems give accept- able performance ...
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Histogram Equalization to Model Adaptation for Robust Speech Recognition
... clean speech models and compensated features in the decoding process of ...clean speech models can be fully adapted into acoustically matched speech models as far as the amount of adaptation data is ...
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An English language speech database at the University of Western Australia
... Successful research and development of practical speech recognition algorithms and systems depends very much on the quantity and quality of speech data available.. [r] ...
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Speech Recognition for English Language Pattern Recognition Approach
... There is statistical method which is widely used for characterizing spectral properties known as Hidden Markov Model. There were two scientist by the name of Baker and Jelinek from Carnegie Mellon University and at IBM ...
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Speech Emotion Recognition Systems: Review
... emotion recognition from speech by incorporating rhythm and temporal ...Emotion Recognition researches are mainly based on applying features like MFCC’s, pitch and ...the speech signal on the ...
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Pauses and the temporal structure of speech
... example, in the preceding sentence, there is much greater cohesion between the words “the”, “various” and “degrees” than between “structure” and the succeeding word “that”. By “cohesion” is meant frequency of ...
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