This Article 
 Bibliographic References 
 Add to: 
Automated Natural Spoken Dialog
April 2002 (vol. 35 no. 4)
pp. 51-56

Traditional menu-driven speech recognition systems force users to learn the machine's jargon, but many people can't or won't navigate such highly structured interactions. AT&T's "How May I Help You?" technology shifts the burden to the machine by requiring it to adapt to human language and understand what people actually say rather than what a system designer expects them to say. For a given task, it is more crucial to recognize and understand some linguistic events than others. The authors have developed algorithms that automatically learn the salient words, phrases, and grammar fragments for a given task far more reliably than other methods.

Allen L. Gorin, Alicia Abella, Tirso Alonso, Giuseppe Riccardi, Jeremy H. Wright, "Automated Natural Spoken Dialog," Computer, vol. 35, no. 4, pp. 51-56, April 2002, doi:10.1109/MC.2002.993771
Usage of this product signifies your acceptance of the Terms of Use.