Guiding CTC Posterior Spike Timings for Improved Posterior Fusion and Knowledge Distillation

Conventional automatic speech recognition (ASR) systems trained from frame-level alignments can easily leverage posterior fusion to improve ASR accuracy and build a better single model with knowledge distillation. End-to-end ASR systems trained using the Connectionist Temporal Classification (CTC) loss do not require frame-level alignment and hence simplify model training. However, sparse and arbitrary posterior spike timings from CTC models pose a new set of challenges in posterior fusion from multiple models and knowledge distillation between CTC models. We propose a method to train a CTC model so that its spike timings are guided to align with those of a pre-trained guiding CTC model. As a result, all models that share the same guiding model have aligned spike timings. We show the advantage of our method in various scenarios including posterior fusion of CTC models and knowledge distillation between CTC models with different architectures. With the 300-hour Switchboard training data, the single word CTC model distilled from multiple models improved the word error rates to 13.7%/23.1% from 14.9%/24.1% on the Hub5 2000 Switchboard/CallHome test sets without using any data augmentation, language model, or complex decoder.Comment: Accepted to Interspeech 201

Foreign equity caps under two types of competition: Bertrand and Cournot

This paper explores foreign equity caps for international joint ventures under different types of competition, i.e., Bertrand and Cournot competition, with product differentiation. We demonstrate that government sets the foreign equity cap at a laxer level under Cournot competition than under Bertrand competition. This result illustrates that the possibility of international joint ventures weakens government's ability to affect firm behavior through the implementation of foreign equity caps.Foreign equity caps Cournot competition Bertrand competiton Product differentiation

Averaged Number of the Lightest Supersymmetric Particles in Decay of Superheavy Particle with Long Lifetime

We calculate the averaged number \nu of the lightest supersymmetric particles (LSPs) in a shower from the decay of superheavy particle X by generalized DGLAP equations. If the primary decayed particles have color charges and the virtuality is around 10^13-10^14 GeV, the averaged number of the LSPs can become O(100). As the result, the upper limit of the mass of the superheavy particle, whose decay can produce the observed abundance of the dark matter, can increase from 10^12 GeV to 10^14 GeV. Since the typical scale of the inflaton mass of the chaotic inflation is around 10^13 GeV, the decay of the inflaton can produce the observed dark matter abundance if the reheating temperature is of order 1 GeV. Even for the standard model particles with virtuality Q\sim 10-100 TeV, the averaged number of the LSPs becomes O(0.1) for gluon, and O(0.01) for Higgs, which strongly constrains the scenario of non-thermal LSP production from the decay of moduli with 10-100 TeV mass.Comment: 9 page

Foreign equity caps for international joint ventures

We analyze foreign equity caps for international joint ventures. We develop a partial equilibrium model in which foreign equity caps are determined endogenously and find an interesting property, named a welfare indifference property i.e., maximization of domestic welfare and that of world welfare are indifferent for the host government. This property also implies that the government is indifferent to the distribution of a JV's profit.

Viscosity and density of methanol/water mixtures at low temperatures

Viscosity and density are measured at low temperatures for three methanol/water mixtures. Viscosity is determined by a modified falling cylinder method or a calibrated viscometer. Density is determined by the volume of each mixture contained in a calibrated glass cell placed in a constant-temperature bath