Context Model Acquisition from Spoken Utterances

Context Model Acquisition from Spoken Utterances

Current systems with spoken language interfaces do not leverage contextual information. Therefore, they struggle with understanding speakers’ intentions. We propose a system that creates a context model from user utterances to overcome this lack of information. It comprises eight types of contextual information organized in three layers: individual, conceptual, and hierarchical. We have impleme...

Learning lexicons from spoken utterances based on statistical model selection

This paper proposes a method for the unsupervised learning of lexicons from pairs of a spoken utterance and an object as its meaning without any a priori linguistic knowledge other than a phoneme acoustic model. In order to obtain a lexicon, a statistical model of the joint probability of a spoken utterance and an object is learned based on the minimum description length principle. This model c...

Learning Physically Grounded Lexicons from Spoken Utterances

Grammatical error detection from English utterances spoken by Japanese

This paper describes methods to recognize English utterances by Japanese learners as accurately as possible and detects grammatical errors from the transcription of the utterances. This method is a building block for the voice-interactive Computer-Assisted Language Learning (CALL) system that enables a learner to make conversation practice with a computer. A difficult point for development of s...

Predicting mild cognitive impairment from spontaneous spoken utterances

INTRODUCTION Trials in Alzheimer's disease are increasingly focusing on prevention in asymptomatic individuals. We hypothesized that indicators of mild cognitive impairment (MCI) may be present in the content of spoken language in older adults and be useful in distinguishing those with MCI from those who are cognitively intact. To test this hypothesis, we performed linguistic analyses of spoken...