For large vocabulary continuous speech recognition systems, the amount of acoustic
training data is of crucial importance. In the past, large amounts of speech were thus …

We present our study on semi-supervised Gaussian mixture model (GMM) hidden Markov
model (HMM) and deep neural network (DNN) HMM acoustic model training. We analyze …

This paper quantifies the value of pronunciation lexicons in large vocabulary continuous
speech recognition (LVCSR) systems that support keyword search (KWS) in low resource …

This paper describes some recent experiments using unsupervised techniques for acoustic
model training in order to reduce the system development cost. The approach uses a …

This paper presents our recent effort that aims at improving our Arabic broadcast news (BN)
recognition system by using thousands of hours of un-transcribed Arabic audio in the way of …

We present a new light supervision method to derive additional acoustic training data
automatically for broadcast news transcription systems. A subset of the TDT corpus, which …

The existing service discovery infrastructure with UDDI as the de facto standard, is limited in
that it does not support more complex searching based on matching business processes …

In this paper, we investigate how to apply graph-based semisupervised learning to acoustic
modeling in speech recognition. Graph-based semisupervised learning is a widely used …

This article describes a new automatic transcription system in the Japanese Parliament
which deploys our automatic speech recognition (ASR) technology. To achieve high …

This paper presents an end-to-end approach for generating readable and clean text directly
from speech signal. While conventional automatic speech recognition (ASR) systems are …