This paper examines tagging models for spontaneous English speech transcripts. We analyze the performance of state-of-the-art tagging models, either generative or discriminative, ...
Vladimir Eidelman, Zhongqiang Huang, Mary P. Harpe...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
In an attempt to improve models of human perception, the recognition of phonemes in nonsense utterances was predicted with automatic speech recognition (ASR) in order to analyze i...
The Human Speechome Project is an effort to observe and computationally model the longitudinal course of language development for a single child at an unprecedented scale. The ide...
Deb Roy, Rupal Patel, Philip DeCamp, Rony Kubat, M...
We propose a canonical model for object classes in aerial images. This model is motivated by the observation that geographic regions of interest are characterized by collections o...