Pairwise secret key agreement based on location-derived common randomnessConference Paper • April 13th, 2016
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Multipartite Intrinsic Non-Locality and Device- Independent Conference Key AgreementConference Paper • January 10th, 2023
AGREEMENT AMONG MULTIPLE LVCSR MODELS — CORRELATION BETWEEN PAIR OF ACOUSTIC MODELS AND CONFIDENCE —Conference Paper • January 9th, 2022
For many practical applications of speech recognition systems, it is quite desirable to have an estimate of confidence for each hypoth- esized word. Unlike previous works on confidence measures, this paper studies features for confidence measures that are extracted from outputs of more than one LVCSR models. More specifically, this paper experimentally evaluates the agreement among the out- puts of multiple Japanese LVCSR models, with respect to whether it is effective as an estimate of confidence for each hypothesized word. The results of experimental evaluation show that the agree- ment between the outputs with two LVCSR models with differ- ent decoders and acoustic models can achieve quite reliable con- fidence. Furthermore, among various features of acoustic models based on Gaussian mixture HMMs, it is concluded that ones such as whether or not to have short pause models, as well as different units in HMMs (e.g., triphone model or syllable model) are the most effective in achieving
Investor Heterogeneity, Investor-Management Agreement and Open Market Share RepurchaseConference Paper • December 5th, 2019
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