Speech-Activated Text Retrieval System for Cellular Phones with Web Browsing Capability

PACLIC 19 / Taipei, taiwan / December 1-3, 200

Chinese Speech Information Retrieval for Questions on Mobile Phone Operation

PACLIC 20 / Wuhan, China / 1-3 November, 200

Contextual awareness, messaging and communication in nomadic audio environments

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1998.Includes bibliographical references (p. 119-122).Nitin Sawhney.M.S

HINDI SPEECH ENABLED WINDOWS APPLICATION USING MICROSOFT SAPI

ABSTRACT People with disability such as visual impaired, elderly for whom it's very hard to identify the screen text and area where the keyboard and mouse may not be an appropriate means of communication between system. So it would be a real relief to have the option to use ears to listen to the contents and use voices to navigate and control the computer systems. Even if sometimes it is for normal people, it would be more comfortable to work with speech enabled applications. Microsoft has designed an interface called SAPI (Speech Application Programming Interface) which supports dynamic speech input and output, and is integrated in our current operating systems. With the API it is possible to develop speech enabled applications without caring about the details of synthesis and recognition. In this paper, a Hindi Speech enabled Windows Application (HSeA) is presented to demonstrate the use of speech-enabled application using Microsoft SAPI in Microsoft Windows Operating Systems

Mobile Cloud Support for Semantic-Enriched Speech Recognition in Social Care

Nowadays, most users carry high computing power mobile devices where speech recognition is certainly one of the main technologies available in every modern smartphone, although battery draining and application performance (resource shortage) have a big impact on the experienced quality. Shifting applications and services to the cloud may help to improve mobile user satisfaction as demonstrated by several ongoing efforts in the mobile cloud area. However, the quality of speech recognition is still not sufficient in many complex cases to replace the common hand written text, especially when prompt reaction to short-term provisioning requests is required. To address the new scenario, this paper proposes a mobile cloud infrastructure to support the extraction of semantics information from speech recognition in the Social Care domain, where carers have to speak about their patients conditions in order to have reliable notes used afterward to plan the best support. We present not only an architecture proposal, but also a real prototype that we have deployed and thoroughly assessed with different queries, accents, and in presence of load peaks, in our experimental mobile cloud Platform as a Service (PaaS) testbed based on Cloud Foundry