Apparatus and methods for speech recognition

Claim 2

Apparatus for recognising words in a predetermined vocabulary comprising means for successively sampling sounds and obtaining respective sets of signals representative of attributes of the sounds, means storing data representing a number of finite state machines one for, and forming an individual model of, each word in the predetermined vocabulary, the data specifying the states which form the finite state machines and assigning a probability function to each state, means for determining from the sets of signals and the probability functions, the probabilities that any given set of signals would be generated if the models produced real sounds and any model was in any given state, means for determining from the probabilities calculated and the properties of the finite state machines the maximum likelihoods that sequences of sound samples represent the predetermined words, and means for providing an output, based on the maximum likelihoods detected, indicating one of the predetermined words as being most likely to have been spoken, characterised in that at least one probability function is assigned to more than one state, and each probability function specifies the probabilities that the signals representative of the attributes of the sounds would assume any observed values if the models produced real sounds and any model was in a state to which that probability function is assigned.

Claim 3

Apparatus according to Claim 1 characterised in that the means storing data stores, for each probability function, a template vector having elements relating to the intensities and/or variances of sounds in respective frequency ranges.

Claim 4

Apparatus according to Claim 1 or 2 characterised in that the means for calculating probabilities comprises means for calculating a distance vector from the probability functions and each set of signals as they occur, each element of the distance vector has a corresponding probability function and is representative of the reciprocal of the probability of observing the current signal set if any finite state machine produced real sounds and occupied a state to which the corresponding probability function had been assigned, and a special purpose logic circuit means constructed to determine the minimum cumulative distances of each state of each finite state machine using the current distance vector.

Claim 7

Apparatus for analysing data relating to the existence of one of a number of conditions, comprising means for receiving sets of signals representing data to be analysed, means for storing data representing a number of finite state machines one for and individually modelling each of the conditions, the data including a number of probability functions, means for determining indicators, from the probability functions and sets of data as they occur representative of the probabilities that any given set of signals would be generated if the models produced real signals and any model was in any given state, and logic circuit means constructed to determine values of minimum cumulative distances of each state of each finite state machine using the said indicators, characterised in that at least one probability function is assigned to more than one of the states of the finite state machines and each specifies the probabilities that-the signals representative of the attributes of data would assume any observed values if the models produced real signals and any model was in a state to which that finite state machine is assigned.

Claim 8

Apparatus for analysing data relating to the existence of one of a number of conditions, comprising means for receiving sets of signals representing data to be analysed, means for storing data representing a number of finite state machines one for and individually modelling each of the conditions, the data including a number of probability functions, means for determining indicators, from the probability functions and sets of data as they occur representative of the probabilities that any given set of signals would be generated if the models produced real signals and any model was in any given state, and logic circuit means constructed to determine values of minimum cumulative distances of each state of each finite state machine using the said indicators, characterised in that at least one probability function is assigned to more than one of the states of the finite state machines and each specifies the probabilities that-the signals representative of the attributes of data would assume any observed values if the models produced real signals and any model was in a state to which that finite state machine is assigned.

Claim 9

Apparatus for recognising words in a predetermined vocabulary comprising means for successively sampling sounds and obtaining respective sets of signals representative of attributes of the sounds, means for storing data representing a number of finite state machines one for, and forming an individual model of, each word in the predetermined vocabulary, the data specifying the states which form the finite state machines and assigning a probability function to each state, means for calculating a distance vector from the probability functions and each set of signals as they occur and for generating a control signal each time a vector has been calculated, each vector being representative of the probabilities that any given set of signals would be generated if the models produced real sounds and any model was in any given state, means for determining, on receipt of one of the control signals, values representative of the minimum cumulative distances of each state of each finite state machine using the current distance vector, and means for providing an output, based on the minimum cumulative distances calculated, indicating one of the predetermined words as being most likely to have been spoken, characterised in that the means for determining values representative of the minimum cumulative distances is a specially constructed logic circuit, at least one probability function is assigned to more than one state, and each probability function specifies the probabilities that the signals representative of the attributes of the sounds would assume any observed values if the models produced real sounds and any model was in a state to which that probability function is assigned.

Claim 10

Apparatus for recognising words in a predetermined vocabulary comprising means for successively sampling sounds and obtaining respective sets of signals representative of attributes of the sounds, means for storing data representing a number of finite state machines one for, and forming an individual model of, each word in the predetermined vocabulary, the data specifying the states which form the finite state machines and assigning a probability function to each state, means for calculating a distance vector from the probability functions and each set of signals as they occur and for generating a control signal each time a vector has been calculated, each vector being representative of the probabilities that any given set of signals would be generated if the models produced real sounds and any model was in any given state, means for determining, on receipt of one of the control signals, values representative of the minimum cumulative distances of each state of each finite state machine using the current distance vector, and means for providing an output, based on the minimum cumulative distances calculated, indicating one of the predetermined words as being most likely to have been spoken, characterised in that the means for determining values representative of the minimum cumulative distances is a specially constructed logic circuit, at least one probability function is assigned to more than one state, and each probability function specifies the probabilities that the signals representative of the attributes of the sounds would assume any observed values if the models produced real sounds and any model was in a state to which that probability function is assigned.

Claim 11

Apparatus according to any of Claims 1 to 3, 5 and 6 characterised in that each finite state machine comprises a plurality of the said states linked by transitions, each state and each transition having a corresponding state and transition penalty, respectively, held as part of the data representing the finite state machines, each transition penalty being a characteristic of the finite state machine of which it is a part and each state penalty depending on the probability function assigned to the corresponding state and on current said sets of signals.

Claim 12

Apparatus according to Claim 7 insofar as dependent on Claim 3 or 6 characterised by means for storing the minimum cumulative distance for each machine, and wherein the logic circuit means is constructed to determine for each transition of a current state a value dependent on the minimum cumulative distance of the originating state of that transition and the transition penalty, to determine the minimum said value and to determine the minimum cumulative distance for the current state from the minimum said value and the state penalty for the current state.

Claim 17

A method according to Claim 10 characterised in that the data defining the states deriving one probability function for each state includes merging some sets of signals for each word according to criteria which relate to suitability for merging to provide data defining the states for that word.

Claim 18

A method according to Claim 11 characterised in that the criteria for merging sets of signals for each word include predetermined maximum and minimum numbers of states for each word.

Claim 19

A method according to Claim 11 or 12 characterised in that successive sets of signals are merged and the suitability of two successive sets for merging is assessed by calculating the logarithm of the ratio of the likelihood that each set of signals for potential merging arose from distinct sets.

Claim 21

Apparatus characterised in that it is arranged to carry out the method of any of Claims 9 to 14.