Speech in Noisy Environments
Performance Evaluation of CMN for Mel LPC based Speech Recognition in Different Noisy Environments
... distributed speech recognizer for real-world applications by employing Cepstral Mean Normalization (CMN) for robust feature ...noisy environments. To realize this objective, Mel- LP based ...
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Speech recognition in reverberant and noisy environments employing multiple feature extractors and i vector speaker adaptation
... technique-based speech recogni- tion systems, and then we combined the recognition re- sults with the help of ROVER (Recognizer Output Voting Error Reduction) to get the best possible recognition re- sults, ...
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Robust emotional speech recognition based on binaural model and emotional auditory mask in noisy environments
... The goal of the acoustic model-based methods, on the other hand, is to tune the models in the training stage to make AMs more matched to emotional speech [10, 11]. Pan et al. [10] have used an adaptation technique ...
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KALAKA-2: a TV Broadcast Speech Database for the Recognition of Iberian Languages in Clean and Noisy Environments
... less speech was available: roughly, the cost doubled when mov- ing from 30-second to 10-second segments, and doubled again when moving from 10-second to 3-second ...
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Automatic recognition of child speech for robotic applications in noisy environments
... human speech while the robot is speaking since otherwise we would end up recognising the robot speech instead of the human ...robot speech - although evaluations showed it is not perfect (see ...
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SPEECH ENHANCEMENT USING PITCH DETECTION APPROACH FOR NOISY ENVIRONMENT
... outstandingly speech recognition ...the noisy speech signal to increase the signal intelligibility and to reduce the listener ...the speech signal when the additive noise cannot be directly ...
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A Noise Estimator with Rapid Adaptation in Variable-Level Noisy Environments
... variable-level noisy environment is ...noise environments, a robust voice activity detector (VAD) is utilized in this paper and it depends on the variation of the spectral energy not on the amount of ...
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Automatic Detection and Recognition of Tonal Bird Sounds in Noisy Environments
... The above-mentioned bird recognition studies per- formed the recognition using a relatively small number of bird species (between two to sixteen), and nearly all studies were performed on clean data. In [14], it was ...
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ENHANCEMENT OF ANIMAL VOCALIZATION USING VARIOUS ALGORITHMS
... least, speech intelligibility. The objective of speech enhancement algorithms is to improve one or more perceptual aspects of noisy speech, most notably, and ...for speech enhancement ...
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Noise Reduction from the speech signal using WP coefficients and Modified Thresholding
... These studies relate the place of articulation of stop consonants to the patterns in transitions of formants observed on spectrograms. It was noted, however, that spectrographic patterns for a particular phoneme ...
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Noise Estimation of Speech Signal using Adaptive Sub -spectral System
... in speech communication, speech and speaker recognition, aid devices for the hearing impaired and numerous other ...applications. Speech is a fundamental means of human ...
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A seed generation technique based on elliptic curvefor providing synchronization in secured immersive teleconferencing
... The purpose of this study is to propose a seed generation and sharing scheme for multimedia encryption based on MVC extension of H.264 standard for immersive teleconferencing. This research proposes a seed generation and ...
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Detecting Speech Repairs Incrementally Using a Noisy Channel Approach
... We have demonstrated an incremental model for finding speech disfluencies in spoken lan- guage transcripts. When we consider com- plete utterances, the incremental model pro- vides identical results to those of a ...
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Noisy training for deep neural networks in speech recognition
... the noisy train- ing approach can be justified in two ways: discriminative noise pattern learning and objective function ...the noisy training scheme works for the DNN model which involves a large number of ...
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Twitter Part-of-Speech Tagging for All: Overcoming Sparse and Noisy Data
... Regarding Twitter part-of-speech tagging, the two most similar earlier papers introduce the ARK tagger (Gim- pel et al., 2011) and T-Pos (Ritter et al., 2011). Both these approaches adopt clustering to handle ...
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Domain adaptation for part of speech tagging of noisy user generated text
... The final 90.3% on the test set outperform the results of Rehbein (2013) by 1.5 percentage points.Our best score also outperforms the ac- curacy obtained with the NCRF++ model. This shows that for classifying ...
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Dynamics and Correlated Noise in Gene Regulation
... This thesis explores the idea of using noise as a tool for understanding gene regulation. Traditionally, cellular noise was considered detrimental because it introduces variability that may prevent a biolog- ical circuit ...
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Reverberation suppression using AdaBoost based EMD in Noisy speech
... Fig. 5 provides the details of simulation plots obtained using EMD only, i.e., de-noising is done with basic EMD. In this plot the estimated signal is obtained by manual selection of IMFs. Fig.6 describes the simulation ...
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Towards a noisy channel model of dysarthria in speech recognition
... for noisy channel models of the neuro-motor interface assuming that the path- way of motor command to motor activity is a lin- ear sequence of ...during speech (Gracco, ...resulting speech has ...
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Speech Compression for Better Audibility using Wavelet Transformation with Adaptive Kalman Filtering
... a speech files spoken in English language is recorded for both male and ...the speech signals in terms of SNR and compression score were observed at different ...based speech Coder’s performance, ...
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