SAMVAAD: speech applications made viable for access-anywhere devices

The proliferation of pervasive devices has stimulated the development of applications that support ubiquitous access via multiple modalities. Since the processing capabilities of pervasive devices differ vastly, device-specific application adaptation becomes essential. We address the problem of speech application adaptation by dialog call-flow reorganisation for pervasive devices with different memory constraints. Given an atomic dialog call-flow A and device memory size m, we present optimal deterministic algorithms, RESEQUENCE and BALANCE-TREE, which minimise the number of questions in the reorganised output call-flow A_m. Algorithms MASQ and MATREE produce C_m, minimally distant from input call-flow A_m while accommodating the memory constraint m. These two minimisation criteria are capable of capturing various usability requirements important in dialog call-flow design. The following observation forms the cornerstone of all the algorithms in this paper: Two grammars g₁ and g₂ comprising of |g₁| and |g₂| elements respectively can be merged into a single grammar g = g₁ × g₂ having |g₁|·|g₂| elements for the sequential case, and g = g₁ + g₂ having |g₁|+|g₂| elements for the tree case. Device-speciific considerations lead us to introduce the concept of an -characterisation of a call-flow, defined as the set of pairs {(m_i,q_i)| ∈ N}, where q_i is the minimum number of questions required for memory size m_i. Each call-flow has a unique, device-independent signature in its -characterisation - a measure of its adaptability. We present SAMVAAD, a system that implements these algorithms on call-flows authored in VXML containing SRGS grammars. The system was tested on an IBM voice browser using a sample airline reservation system call-flow reorganised for memories ranging from 64 MB to 210 KB. We ran an experiment with 14 users to obtain feedback on the usability of the adapted call-flows.