SAIC today made Arabic and Spanish versions of its Omnifluent Travel machine translation (MT) app available at the iTunes store for free, joining a growing category of handheld MT and mobile interpreting offerings. While online MT software has long offered computer users translation at their fingertips, this technology on mobile phones brings language technology into real-life situations, such as traveling to distant lands.

The Omnifluent Travel app accepts either keyboard input on the iPhone or spoken requests using SAIC’s automated speech recognition (ASR) technology. Both apps use the company’s MT engine in the cloud for bidirectional translation to or from English, and produce both a textual and spoken version of the translation. Translation requires a connection to the web.

When the phone doesn’t have web access, the app allows one-way communication of emergency, health, dining, and transportation issues through a set of more than 100 phrases that should prove useful for travelers. For example, the set expressions run the gamut from “call a doctor!” to “where is the nearest all-night drug store?” When the iPhone is connected to the cloud, users can record, save, and even post-edit translations of expected interactions, such as “please take me to the Jeddah Hilton” to play for the cab driver at the airport.

We spoke with SAIC Senior Vice President Jonathan Litchman about the product and his company’s plans for the technology. He told us that the major reason for making the app available for free was to showcase the company’s ASR and MT technology to a broader community than the usual professional and government workers who use SAIC’s products. Longer term, the Travel App is a test bed for future versions tailored to the needs of a specific vertical. SAIC has already produced a version for the New Jersey Association of County and City Health Officials to support the group’s influenza outreach program to Spanish-speaking residents of the state.

Litchman acknowledged that Omnifluent Travel is a first-version product in explaining an input-output issue that we noticed with the Arabic version of the application. Because it was trained with speakers in Egypt and the Gulf States, the speech recognition component stumbled with our Algerian-born test speaker. Also, the MT outputs classic Arabic, not the dialect used in North Africa. Litchman said that the broader community that will be reached through the iTunes store – and through future Android and Windows Mobile versions – should increase the app’s ability to deal with other dialects and regional accents. However, classical Arabic will be the preferred dialect until there’s demand for other variants. More.

See: Common Sense Advisory