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NAACL
2007
13 years 6 months ago
Virtual Evidence for Training Speech Recognizers Using Partially Labeled Data
Collecting supervised training data for automatic speech recognition (ASR) systems is both time consuming and expensive. In this paper we use the notion of virtual evidence in a g...
Amarnag Subramanya, Jeff A. Bilmes
ICASSP
2011
IEEE
12 years 8 months ago
A paired test for recognizer selection with untranscribed data
Traditionally, the use of untranscribed speech has been restricted to unsupervised or semi-supervised training of acoustic models. Comparison of recognizers has required labeled d...
Bhiksha Raj, Rita Singh, James Baker
NIPS
2007
13 years 6 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury
CSL
2002
Springer
13 years 4 months ago
Lightly supervised and unsupervised acoustic model training
The last decade has witnessed substantial progress in speech recognition technology, with todays state-of-the-art systems being able to transcribe unrestricted broadcast news audi...
Lori Lamel, Jean-Luc Gauvain, Gilles Adda
CCS
2005
ACM
13 years 10 months ago
Keyboard acoustic emanations revisited
We examine the problem of keyboard acoustic emanations. We present a novel attack taking as input a 10-minute sound recording of a user typing English text using a keyboard, and t...
Li Zhuang, Feng Zhou, J. D. Tygar