[PDF] Top 20 Multiple Approaches to Robust Speech Recognition

... MULTIPLE APPROACHES TO ROBUST SPEECH RECOGNITION MULTIPLE APPROACHES TO ROBUST SPEECH RECOGNITION Richard M Stern, Fu Hua Liu, Yoshiaki Ohshima, Thomas M Sullivan, Alejandro Acero* D e p a r t m e n t[.] ... See full document

... the speech signal. It is desired that the parameterizations are robust to noise and variations in channel, device, speaker, session and other adverse environments and capture the spectral dynamics of ... See full document

... HEQ approaches are very effective in matching the global feature statistics of the test (or noisy) speech to that of the training (or reference) set, we found that some undesired sharp peaks or valleys of ... See full document

... of speech recognition ...feature-based approaches. In model- based approaches, compensation is performed on the pre-trained recognition model parameters so that the modified ... See full document

... environments. Speech enhancement methods can be classified into two main categories ...three approaches, noise resistant features, feature normalization, and feature ...approach, robust signal ... See full document

... usual speech recognition tasks require the whole phonetic units in acoustic ...domain-constrained speech recognition task such as digit recognition task which employs a small number of ... See full document

... clean speech signal uttered by a female speaker, taken at time frames of 300 ms, 700 ms and 2100 ...voiced speech, then each frequency channel excited by that signal will have a high similarity to itself ... See full document

... propose robust distant speech recognition by combining multiple microphone-array processing with position-dependent cep- stral mean normalization ...the recognition stage, the system ... See full document

... on multiple recording sessions of one and the same speaker yields a reasonable performance and that a session- independent system recognizes test data from unseen sessions more robustly than a similarly large ... See full document

... in-car recognition sys- tem, we develop an effective algorithm for adapting the re- gression parameters to different driving ...train multiple hidden Markov models (HMMs) over the synthesized ...in-car ... See full document

... Early works of combining classifiers were suggested in [2] combining linear and K-nearest neighbor classifier. The approach received greater focus and was described more systematically in [3]. According to [3], ... See full document

... An attractive alternative to correlating the phone hypotheses from the recognizers is to construct word hypotheses from the phone recognizer output and compare these hypotheses with those output by the word recognizer. ... See full document

... determine speech and non-speech ...between speech and ...of speech samples at each frequency is different from that of ...of speech is high for many values but for speech always ... See full document

... reverberated speech samples can be simulated by converlution according to ...other approaches for room acoustics simulation [19], it generates a large number of virtual rooms for the study of the relations ... See full document

... for Speech-based human-machine communications are no longer constrained to the detection of the users’ message and to speech synthesis but also the automatic characterization of the users has been gaining ... See full document

... of speech. The first 15 seconds of speech from each test conversation was used for test ...speaker recognition has targeted the impact of background noise through filtering techniques such as ... See full document

... sufficient recognition accuracy, even in the presence of surrounding ...the speech recognition accuracy drastically degrades when the microphone is placed far from the ...noise robust ... See full document

... In our proposed method, an HMM for each word in the dictionary and an HMM for sudden noise are created. Then, these models are combined to create an FHMM for each word. We propose an extension to employ dynamic features ... See full document

... The Aurora 2 task defines two different training modes: training on clean condition only, and training on multi- condition which include both clean and noisy conditions. Experiments with training on both conditions are ... See full document

... Recent Progress in Robust Vocabulary Independent Speech Recognition Recent Progress in Robust Vocabulary Independent Speech Recognition Hsiao Wuen Hon and Kai Fu Lee School o f Computer Science Carneg[.] ... See full document