Building Speech Applications Just Got Easier: AT&T Releases Speech API
false Speech interfaces are becoming de rigueur because users find them easy to use. But implementing these interfaces is not easy. Speech technologies are complex and require expert knowledge. AT&
AT&T Labs Fellowship Award Winner
; in adult dialog, provocative hostility. A human instantly interprets the correct meaning from ...
AT&T WATSON(SM) Voice Recognition Technology & Speech API
true AT&T WATSON, automatic speech recognition, speech technologies AT&T WATSONSM is a general-purpose engine that performs a variety of speech and analysis tasks, including automatic speech r
PLOW: A Collaborative Task Learning Agent
years, he has been focussing on producing end-to-end working dialog systems that can connect everyday ...
AT&T Natural VoicesTM Text-to-Speech
Natural Voices is AT&T's state-of-the-art text-to-speech product, taking text and producing natural-sounding, synthesized speech in a variety of voices and languages.
Video - Indexing and Representation (Metadata)
Video and multimedia indexing and representations (i.e. metadata), their production, and use. Links to projects within the AT&T Video and Multimedia Technologies and Services Research Department.
Visualizing Empirical Dialog Trajectories
1 VISUALIZING EMPIRICAL DIALOG TRAJECTORIES Jeremy Wright* Member, IEEE, Alicia Abella, and David Kapilow Abstract — Automated spoken dialog systems require systematic procedures
Applying POMDPs to Dialog Systems in the Troubleshooting Domain
Applying POMDPs to Dialog Systems in the Troubleshooting Domain Jason D. Williams AT&T Labs ... ) to a commercial dia- log domain: troubleshooting. In the trou- bleshooting domain, a spoken
Learning the structure of task-driven human-human dialog
Srinivas Bangalore, Srinivas Bangalore, Srinivas Bangalore Learning the structure of taskdriven humanhuman dialog IEEE Transactions of Audio Speech and Language Processing special issue on New Approaches to Statistical Speech and Text Processing 7 16 1249-1259
Incremental parsing models for dialog task structure
Srinivas Bangalore, Srinivas Bangalore Incremental parsing models for dialog task structure Proceedings of the Meeting of the European Chapter of the Association for Computational Linguistics EACL