Cardiologist-level arrhythmia detection with convolutional neural networks
We develop an algorithm which exceeds the performance of board certified cardiologists in
detecting a wide range of heart arrhythmias from electrocardiograms recorded with a single …
detecting a wide range of heart arrhythmias from electrocardiograms recorded with a single …
The architectural implications of facebook's dnn-based personalized recommendation
The widespread application of deep learning has changed the landscape of computation in
data centers. In particular, personalized recommendation for content ranking is now largely …
data centers. In particular, personalized recommendation for content ranking is now largely …
An overview of end-to-end automatic speech recognition
D Wang, X Wang, S Lv - Symmetry, 2019 - mdpi.com
Automatic speech recognition, especially large vocabulary continuous speech recognition,
is an important issue in the field of machine learning. For a long time, the hidden Markov …
is an important issue in the field of machine learning. For a long time, the hidden Markov …
Backpropagation for energy-efficient neuromorphic computing
Solving real world problems with embedded neural networks requires both training
algorithms that achieve high performance and compatible hardware that runs in real time …
algorithms that achieve high performance and compatible hardware that runs in real time …
End-to-end attention-based large vocabulary speech recognition
Many state-of-the-art Large Vocabulary Continuous Speech Recognition (LVCSR) Systems
are hybrids of neural networks and Hidden Markov Models (HMMs). Recently, more direct …
are hybrids of neural networks and Hidden Markov Models (HMMs). Recently, more direct …
Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
[PDF][PDF] Efficient emotion recognition from speech using deep learning on spectrograms.
A Satt, S Rozenberg, R Hoory - Interspeech, 2017 - isca-archive.org
We present a new implementation of emotion recognition from the para-lingual information
in the speech, based on a deep neural network, applied directly to spectrograms. This new …
in the speech, based on a deep neural network, applied directly to spectrograms. This new …
Device placement optimization with reinforcement learning
A Mirhoseini, H Pham, QV Le… - International …, 2017 - proceedings.mlr.press
The past few years have witnessed a growth in size and computational requirements for
training and inference with neural networks. Currently, a common approach to address …
training and inference with neural networks. Currently, a common approach to address …
[PDF][PDF] Audio augmentation for speech recognition.
Data augmentation is a common strategy adopted to increase the quantity of training data,
avoid overfitting and improve robustness of the models. In this paper, we investigate audio …
avoid overfitting and improve robustness of the models. In this paper, we investigate audio …
Achieving human parity in conversational speech recognition
Conversational speech recognition has served as a flagship speech recognition task since
the release of the Switchboard corpus in the 1990s. In this paper, we measure the human …
the release of the Switchboard corpus in the 1990s. In this paper, we measure the human …