[PDF] Top 20 Language Modeling Through Neural Networks to Increase Performance of Speech Recognition System

Language Modeling Through Neural Networks to Increase Performance of Speech Recognition System

... Language model estimates the probability distributions of various linguistic units or their composites. Availability of large amount of training data (i.e., text) has led to improved quality of SLMs. This, in ... See full document

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EVALUATION OF INTRUSION DETECTION TECHNIQUES IN MOBILE AD HOC NETWORKS

... of speech recognition engine which is the latest addition to Carnegie Mellon University’s (CMU) repository of Sphinx speech recognition ...digit speech recognition using Java TM ... See full document

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Recurrent neural network language model adaptation for multi-genre broadcast speech recognition and alignment

... multi-genre speech recognition and ...an increase in F–measure of about ...ASR system as the text LDA features need to be extracted from a first- pass ASR system and used for RNNLM ... See full document

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Speech Recognition using MFCC and Neural Networks

... use speech to interact with machines also. That is why, automatic speech recognition has gained a lot of ...for speech recognition exist like Dynamic Time Warping (DTW), Hidden Markov ... See full document

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Speech Emotion Recognition Using Convolutional Recurrent Neural Networks with Attention Model

... In this paper, a novel approach based on the combination of distributed Convolutional and Recurrent Neural Networks (CRNN) together with an attention mechanism has been proposed. Experimental results give ... See full document

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Modeling of Speech Recognition Using Artificial Neural Network

... the networks, Neural Network toolbox of MATLABR2015a was ...The performance was evaluated by using mean square error as the ...its performance does not diminish as rapidly as compared to ... See full document

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Recognition of sign language using neural networks

... to recognition of handshapes are described in the papers by Kramer and ...this recognition hyper-sphere around each beacon and re-enter it in order to repeat a ...the system to send the completed ... See full document

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Lexicon-Free Conversational Speech Recognition with Neural Networks

... recurrent neural network (DBRNN) to directly map acoustic input to characters using the CTC loss function introduced by Graves and Jaitly ...character-level language model (CLM), whereas previous work ... See full document

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Discrete Wavelet Transforms and Artificial Neural Networks for Recognition of Isolated Spoken Words

... Speech recognition is a fascinating application of Digital Signal Processing and has many real-world ...a speech recognition system is developed for isolated spoken words using Discrete ... See full document

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Noisy training for deep neural networks in speech recognition

... in modeling state emission distributions, when compared to the conventional GMM, has been discussed in some previous publications, ...of speech signals from primitive levels to high ...miserable ... See full document

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Issues in developing LVCSR System for Dravidian Languages: An Exhaustive Case Study for Tamil

... effect speech recognition performance are varied, all the sentences in the test set have been included in the LM and in the lexicon to avoid OOV (Out Of Vocabulary) ...drastic performance drop ... See full document

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Augmentation of Local, Global Feature Analysis for online Character Recognition System for Telugu Language using Feed Forward Neural Networks (FFNN)

... level.The recognition accuracy in this Hybrid approach is ...character recognition using SVM,a two stage method is adopted ...overall recognition accuracy is ...the recognition accuracy is 71% ... See full document

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Cross Lingual Language Modeling with Syntactic Reordering for Low Resource Speech Recognition

... cross-lingual language modeling for transcribing source resource- poor languages and translating them into tar- get resource-rich languages if ...the speech recognition performance of ... See full document

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Recurrent neural network based language model for large vocabulary continuous Tamil language speech recognition system

... Recurrent neural networks histories of the occurrence of h are similar, but n-grams assume exact match of ...Recurrent neural network based language ...recurrent neural network based ... See full document

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Sign Language Recognition using Hybrid Neural Networks

... expert system is applied for 22 signs with more than 95% results ...Sign Language recognition ...Sign Language using 5100 ...the performance along with Hidden Markov Models (HMMs) ... See full document

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Sign Language Recognition System with Speech Output

... of neural networks, which have shown to have an accuracy of as much as ...[1]. Neural networks used for computer vision applications require a lot of high-quality ... See full document

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Artificial Intelligence for Speech Recognition Based on Neural Networks

... Speech recognition or speech to text includes capturing and digitizing the sound waves, transfor- mation of basic linguistic units or phonemes, constructing words from phonemes and contextually ... See full document

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Intelligence Agent Device for E Learning

... go through the search engine via recorder (microphone) by speaking name of any song or poem to get desired ...project system is providing useful informative solution for e-learning inside house or school ... See full document

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Speech Recognition for English Language Pattern Recognition Approach

... The Speech is most prominent & primary mode of Communication among of human ...interface. Speech has potential of being important mode of interaction with computer ...voice recognition and also ... See full document

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Microphone Arrays and Neural Networks for Robust Speech Recognition

... vIicrophone Arrays and Neural Networks for Robust Speech Recognition vIicrophone Arrays and N e u r a l N e t w o r k s for R o b u s t S p e e c h R e c o g n i t i o n C Che +, Q Lin +, J Pearson*,[.] ... See full document

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