Jonathan Raiman

DeepType: Multilingual Entity Linking by Neural Type System Evolution

2018 · arXiv (Cornell University)

The wealth of structured (e.g. Wikidata) and unstructured data about the world available today presents an incredible opportunity for tomorrow's Artificial Intelligence. So far, integration of these two different modalities is a difficult process, involving …

Generative adversarial simulator

2021 · International Journal of Artificial Intelligence and Machine Learning

Knowledge distillation between machine learning models has opened many new avenues for parameter count reduction, performance improvements, or amortizing training time when changing architectures between the teacher and student network. In the case of reinforcement …

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

2015 · arXiv (Cornell University)

We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages. Because it replaces entire pipelines of hand-engineered components with neural networks, end-to-end learning …

Deep Voice: Real-time Neural Text-to-Speech

2017 · arXiv (Cornell University)

We present Deep Voice, a production-quality text-to-speech system constructed entirely from deep neural networks. Deep Voice lays the groundwork for truly end-to-end neural speech synthesis. The system comprises five major building blocks: a segmentation model …

Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence\n Learning

2017 · arXiv (Cornell University)

We present Deep Voice 3, a fully-convolutional attention-based neural\ntext-to-speech (TTS) system. Deep Voice 3 matches state-of-the-art neural\nspeech synthesis systems in naturalness while training ten times faster. We\nscale Deep Voice 3 to data set sizes unprecedented …