Doshisha University (Private)

Research background and goals
The world is globalizing and opportunities to communicate with people speaking different languages are increasing. For computers
and robots with a different language recognition mechanism than humans, opportunities are also increasing to give them various
instructions by spoken language (voice) and receive information from them.
Spoken language is said to be situation dependent, there are many omitted items easily presumed from the situation where the
conversation is taking place, and there is also much ungrammatical speech because of “thinking while speaking, speaking while
thinking” speech behavior. What kind of effect do the characteristics of this spoken language have when trying to communicate with
foreigners that have differing language media and computers and robots that have differing language recognition mechanisms?
Conversely, in what way can we accurately and efficiently establish communication with a subject that differs in these language
media and language recognition mechanisms in a spoken language accessible to ourselves?
We are searching for mechanisms to establish such spoken language communication and researching and developing technologies
for it. Specifically, we are researching topics such as e-learning to support efficient foreign language learning using information
processing technologies, automatic evaluation technologies to accurately measure communication abilities in foreign languages,
speech translations systems by computers to assist communication with foreigners via spoken language, and a speech dialogue
system that enables computers and robots to understand spoken language and generate speech. For this, we must have spoken
language communication science to search for mechanisms to establish spoken language communication along with research and
development of speech recognition, speech synthesis, and natural language processing technologies.
Approach and methods to solve these issues
As a technique for natural language processing, a rule-based approach to develop processing rules based on developer’s
introspection has been primarily used in the past. A rule-based approach is a valuable knowledge source that concentrates the many
years of experience of those developers, but for a large-scale system, maintaining uniformity and maintenance are difficult issues
because many developers are involved. With the increases in computer processing ability and corpora (texts with added information
such as the part of speech, etc.) useable by computers, a corpus-based approach, an approach to automatically acquire knowledge
by machine learning from corpora, is attracting attention. Centered on a corpus-based approach that applies machine learning
techniques to foreign language learner’s corpora, speech databases, and parallel translation examples, we are researching and
developing e-learning systems and speech dialogue systems with robots.
The corpus-based approach is a powerful approach to natural language processing and spoken language processing, but this does
not mean a corpus-based approach is good at everything. How to incorporate the natural knowledge of humans is also an important
research theme. We are advancing research on how humans understand spoken language.
Specific research themes