84 citations · 224 across the 6 of their papers we have counts for
6 papers
Language Model Cascades
David Dohan, Winnie Xu, Aitor Lewkowycz +9
Prompted models have demonstrated impressive few-shot learning abilities. Repeated interactions at test-time with a single model, or the composition of multiple models together, fu…
Deep Probabilistic Programming
Dustin Tran, Matthew D. Hoffman, Rif A. Saurous +3
We propose Edward, a Turing-complete probabilistic programming language. Edward defines two compositional representations---random variables and inference. By treating inference as…
AutoMOS: Learning a non-intrusive assessor of naturalness-of-speech
Brian Patton, Yannis Agiomyrgiannakis, Michael Terry +3
Developers of text-to-speech synthesizers (TTS) often make use of human raters to assess the quality of synthesized speech. We demonstrate that we can model human raters' mean opin…
CNN Architectures for Large-Scale Audio Classification
Shawn Hershey, Sourish Chaudhuri, Daniel P. W. Ellis +10
Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of…
Scalable Learning of Non-Decomposable Objectives
Elad ET. Eban, Mariano Schain, Alan Mackey +3
Modern retrieval systems are often driven by an underlying machine learning model. The goal of such systems is to identify and possibly rank the few most relevant items for a given…
Trainable Frontend For Robust and Far-Field Keyword Spotting
Yuxuan Wang, Pascal Getreuer, Thad Hughes +2
Robust and far-field speech recognition is critical to enable true hands-free communication. In far-field conditions, signals are attenuated due to distance. To improve robustness…