This paper describes the facilities of Converser for Healthcare 4.0, a highly interactive speech translation system which enables users to verify and correct speech recognition and machine translation. Corrections are presently useful for real-time reliability, and in the future should prove applicable to offline machine learning. We provide examples of interactive tools in action, emphasizing semantically controlled back-translation and lexical disambiguation, and explain for the first time the techniques employed in the tools’ creation, focusing upon compilation of a database of semantic cues and its connection to third-party MT engines. Planned extensions of our techniques to statistical MT are also discussed.

This paper reports on three business opportunities encountered by Spoken Translation, Inc., a developer of software systems for automatic spoken translation: (1) a healthcare organization needing improved communications between limited-English patients and their caregivers; (2) a networking and communications firm aiming to add UN-style simultaneous interpreting to their telepresence facilities; and (3) the retail arm of a device manufacturer hoping to enable more effective in-store consulting for customers with imperfect command of an outlet's native language. None of these openings has yet led to substantial business, but one remains in negotiation. We describe how the business introductions came to us; the proposed use cases; demonstrations, presentations, tests, etc.; and issues/challenges. We also comment on early consumer-oriented products for spoken language translation. The aim is to provide a snapshot of one company's business possibilities and challenges at the dawn of the era of automatic interpreting.

Spoken Translation, Inc. (STI) of Berkeley, CA has developed a commercial system for interactive speech-to-speech machine translation designed for both high accuracy and broad linguistic and topical coverage. Planned use is in situations requiring both of these features, for example in helping Spanish-speaking patients to communicate with English-speaking doctors, nurses, and other health-care staff.