Speech Enhancement Using Neural Networks
Single-Channel Speech Enhancement Based on Deep Neural Networks
... that, using less-engineered features like log-magnitude spectrogram performs reasonably well while requires much fewer computations compared to highly-engineered features, and it is also relatively easy to take ...
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Evaluation of Mixed Deep Neural Networks for Reverberant Speech Enhancement
... Abstract: Speech signals are degraded in real life environments, product of background noise or ...recurrent neural networks, especially those with short and long term memory (LSTM), have presented ...
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LOW-LATENCY SINGLE CHANNEL SPEECH ENHANCEMENT USING U-NET CONVOLUTIONAL NEURAL NETWORKS
... perceptual speech quality/intelligibility and processing time performance comparison of the baseline methods and proposed method on the test data as shown in Table ...of speech quality/intelligibility but ...
Speech Enhancement Using Deep Neural Network
... of speech signals during communication are generally corrupted by the surrounding ...Corrupted speech signals therefore to be enhanced to improve quality and ...of speech processing, much effort has ...
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Noise reduction using neural lateral inhibition for speech enhancement
... noise using multilayer lateral inhibitory spiking neural ...artificial neural networks, the lateral inhibitory based SNN does not need to train with ...the speech element from the noise ...
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Speech dereverberation for enhancement and recognition using dynamic features constrained deep neural networks and feature adaptation
... for speech dere- verberation for both speech enhancement and ASR ...DNN-based speech coefficient mapping, paral- lel training data of reverberant speech (observation) and clean ...
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SERGAN : speech enhancement using relativistic generative adversarial networks with gradient penalty
... generative neural networks which can directly map the raw noisy speech wave- form to the underlying clean speech ...raw speech waveform en- hancement ...
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Speech enhancement using deep learning
... One of the most efficient implementation of the Recurrent Neural Networks are the Long Short-Term Memory (LTSM). The LSTM contains special units called memory blocks in the recurrent hidden layer. As it can ...
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Speech emotion recognition with early visual cross modal enhancement using spiking neural networks
... through speech. Spiking Neural Networks (SNN) have demonstrated as a promising approach in machine learning and pattern recognition tasks such as handwriting and facial expression ...in speech ...
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AUTOMATED SPEECH RECOGNITION OF ISOLATED WORDS USING NEURAL NETWORKS
... Keywords: Speech recognition; formant frequencies; zero crossing rate; neural ...Automated Speech Recognition (ASR) is a popular and challenging area of research in developing human computer ...
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Development of Vietnamese Speech Synthesis System using Deep Neural Networks
... in speech coding ...in speech synthesis as well ...sized speech of HMM-Based Text-to-Speech ...DNN-Based Speech Synthesis and got improvement of synthesized speech qua- lity (see ...
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Speech Enhancement Using Neural Network
... out using the ADALINE in the time ...sound using a training set of isolated words spoken by different ...by using backpropogation algorithm. A total of 100 speech samples consisting of 10 ...
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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 Model ...how ...
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Using Convolutional Neural Networks to Classify Hate Speech
... and neural network archi- tectures could be extended in several ways: The word2vec embeddings used here were built on skip-grams that predict the context words using the current ...
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Speech Emotion Recognition using Convolutional Neural Networks
... Although speech modality conveys a large portion of the emotional information, it is not sufficient for recognizing affective states of humans in daily-life ...to speech, people use other paralinguistic ...
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Discriminating Neutral and Emotional Speech using Neural Networks
... from speech signals with models for neutral speech as ...emotional speech is produced by the hu- man speech production mechanism, the emotion information is expected to lie in the features of ...
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Synthetic Speech Detection Using Deep Neural Networks
... implemented using neural network models, which requires minimal specialist ...execution using several parallelization methods and propose an implementation with impressive ...
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Automatic image quality enhancement using deep neural networks
... the neural network image enhancement re- search using similar method has not been extensively ...time enhancement, added some limitations for the choice of evaluated ...
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Performance Enhancement of RSA Algorithm Using Artificial Neural Networks
... A neural network is a machine that is designed to model the way in which the brain performs a particular ...by using electronic components or is simulated in software on a digital ...A neural network ...
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Neural Speech Translation using Lattice Transformations and Graph Networks
... Abstract Speech translation systems usually follow a pipeline approach, using word lattices as an intermediate ...for speech trans- lation through lattice transformations and neu- ral models based on ...
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