Title: Adaptation for Soft Whisper Recognition Using a Throat Microphone
Speaker: Szu-Chen Stan Jou

Abstract: In this talk, we report our work on recognizing soft whispery speech
which is recorded with a throat microphone.
The goal is to provide a noise-robust way to communicate privately.
Our approach applies various adaptation methods to this task.
Since the amount of adaptation data is small and the testing data is very 
different from the training data, a series of adaptation methods is necessary.
We will discuss our combination of adaptation methods, which include
maximum likelihood linear regression, feature-space adaptation,
and re-training with downsampling, sigmoidal low-pass filter,
or linear multivariate regression.