Multiframe Deep Neural Networks for Acoustic Modeling

Acoustic landmarks contain more information about the phone string ...

In this work, experiments are conducted on the TIMIT corpus, with both Gaussian mixture model (GMM) and deep neural network (DNN)-based ASR systems, and it is ...

Speaker Adaptive Training of Deep Neural Network Acoustic Models ...

Abstract—In acoustic modeling, speaker adaptive training. (SAT) has been a long-standing technique for the traditional. Gaussian mixture models (GMMs).

A deep neural network model for multi-view human activity recognition

The model comprised pre-trained convolutional neural networks (CNNs), attention layers, long short-term memory networks with residual learning ( ...

combining deep neural networks and beamforming for real-time

This work presents a multi-channel speech enhancement algorithm using a neural network combined with beamforming deployed real- time on a wireless acoustic ...

Deep Learning for Speech and Language Processing Applications

... depth of the network allows useful representations to be learned. For example, in acoustic modeling, the ability of deep architectures to disentangle multiple ...

Meta-neural-network for real-time and passive deep-learning-based ...

Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Process. Mag. 29, 82 ...

Deep Neural Network acoustic models for ASR by Abdel-rahman ...

There are two views of understanding the learning of a multi-layer generative neural network model: the directed view and the undirected view. In the directed ...

(PDF) Deep Neural Networks: Another Tool for Multimedia

Multiframe Deep Neural Networks for Acoustic Modeling · 2013 English. Job Scheduling for Cloud Computing Using Neural Networks. Communications and Network.

Speaker adaptation of deep neural network acoustic models using ...

The GMM hidden Markov model (GMM-HMM) approach has been one of the most common technique in ASR systems for many decades. Speaker adaptation is ...

Multi-frame factorisation for long-span acoustic modelling – Projects ...

& King, S. EPSRC. 1/05/11 → 31/07/16. Project: Research. Models 100%. Speech Synthesis 84%. Deep Neural Network 71%. Speech Recognition 63%. Hidden Markov ...

Adaptive Multi-Column Deep Neural Networks with Application to ...

Stacked sparse denoising auto-encoders (SSDAs) have recently been shown to be successful at removing noise from corrupted images. However, like most denoising ...

AcousticIA, a deep neural network for multi-species fish detection ...

acoustic cameras, or imaging sonars, are high-potential devices for many applications in aquatic ecology, notably for fisheries management and[...]

Data Augmentation for Deep Neural Network Acoustic Modeling

In this paper we focus on data augmentation approaches to acoustic modeling using deep neural networks (DNNs) for au- ... After data augmentation, multiple ...

Forecasting Time Series with Deep Neural Networks - YouTube

Deep Learning Adventures - TensorFlow In Practice - Session 9 Join us for our 9th adventure in Deep Learning! Just bring your curiosity and ...

Deep convolutional neural networks for acoustic modeling in low...

Convolutional Neural Networks (CNNs) have demonstrated powerful acoustic modelling capabilities due to their ability to account for ...

Multi-layer perceptron vs deep neural network - Cross Validated

One can consider multi-layer perceptron (MLP) to be a subset of deep neural networks (DNN), but are often used interchangeably in literature ...

large scale deep neural network acoustic modeling with - OpenReview

supervised training data and deep neural networks acoustic models with large state inventories. Applying an “island of confidence” fil- tering heuristic to ...

Acoustic Modelling | Papers With Code

We present a deep neural network based singing voice synthesizer, inspired by the Deep Convolutions Generative Adversarial Networks (DCGAN) architecture.