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This paper introduces a discriminative training for language models (LMs) by leveraging phoneme similarities estimated from an acoustic model. To train an LM discriminatively, we needed the correct word sequences and the recognized results that Automatic Speech Recognition (ASR) produced by processing the utterances of those correct word sequences. But,(More)
We applied mobile computing to community support and explored mobile computing with a large number of terminals. This article reports on the Second International Conference on Multiagent Systems (ICMAS'96) Mobile Assistant Project that was conducted at an actual international conference for multiagent systems using 100 personal digital assistants (PDAs) and(More)
This paper presents a strategy for efficiently selecting informative data from large corpora of untranscribed speech. Confidence-based selection methods (i.e., selecting utterances we are least confident about) have been a popular approach, though they only look at the top hypothesis when selecting utterances and tend to select outliers, therefore, not(More)
Microwave-assisted extraction using 1M KOH/methanol (alkaline-MAE) in combination with solid-phase extraction treatment was developed and applied to polycyclic aromatic hydrocarbons (PAHs) in a sediment sample. Although various conditions were examined (100 or 150 degrees C for 10 or 30 min), comparable concentrations of PAHs to those obtained by(More)
Brown rice powder certified reference material, NMIJ CRM 7504-a, for the analysis of pesticide residues was developed by the National Metrology Institute of Japan, part of the National Institute of Advanced Industrial Science and Technology. Brown rice sample was harvested to contain the pesticides such as etofenprox and fenitrothion, and that was collected(More)
We have investigated the differences in response ratios of native polycyclic aromatic hydrocarbons (native PAHs)/13C-labeled PAHs (13C-PAHs) and of native PAHs/deuterium-labeled PAHs (PAHs-d) in a calibration solution containing at trace concentrations (< 1 microg mL(-1)) by gas chromatography-mass spectrometry. Only the ratios of native PAHs/PAHs-d(More)
This paper introduces a method to train an error-corrective model for Automatic Speech Recognition (ASR) without using audio data. In existing techniques, it is assumed that sufficient audio data of the target application is available and negative samples can be prepared by having ASR recognize this audio data. However, this assumption is not always true.(More)