Abstract: A distributed voice recognition system (500) and method employs principles of bottom-up (i.e., raw input) and top-down (i.e., prediction based on past experience) processing to perform client-side and server-side processing by (i) at the client-side, replacing application data by a phonotactic table (504); (ii) at the server-side, tracking separate confidence scores for matches against an acoustic model and comparison to a grammar; and (iii) at the server-side using a contention resolver (514) to weight the client-side and server-side results to establish a single output which represents the collaboration between client-side processing and server-side processing.

Abstract: A system and method for automatic recognition of foreign speakers by performing analysis of a speech sample to produce a signal representative thereof and attempting to match the representative signal to one of a plurality of predetermined sounds to produce recognition; and determining whether a gap exists in a table of predetermined sounds in a predetermined language and, if a gap exists, substituting for matching a sound from a position in the table near the gap. This automatic substitution of known foreign pronunciation characteristics improves and modifies the output from standard, monolingual automatic speech recognition. There is no requirement to implement either adaptation or to impose additional manual modification of the baseform pool on the application developer. In addition, the danger of increased ambiguity is removed by introducing an explicit accent and/or language checker which queries known differences across accents.

Abstract: A method and apparatus for updating a speech model on a multi-user speech recognition system with a personal speech model for a single user. A speech recognition system, for instance in a car, can include a generic speech model for comparison with the user speech input. A way of identifying a personal speech model, for instance in a mobile phone, is connected to the system. A mechanism is included for receiving personal speech model components, for instance a BLUETOOTH connection. The generic speech model is updated using the received personal speech model components. Speech recognition can then be performed on user speech using the updated generic speech model.