Canon Kabushiki Kaisha

Robert Alexander Keiller

Eli Tzirkel-Hancock

Julian Richard Seward

David Llewellyn Rees

Nicolas Fortescue

Nicholas David Fortescue

A method for matching an input pattern with a number of stored reference patterns using a dynamic programming matching technique is described. The reference patterns of a reference signal which are at the end of a dynamic programming path for a current input pattern are listed in an active list. The dynamic programming paths are propagated by processing the reference patterns on the active list, and a new active list is generated for the succeeding input pattern. The amount of processing required for each pattern on the active list is reduced by using a pointer which identifies the reference pattern which is the earliest in the sequence of patterns of the current reference signal listed on the new active list during the processing of a preceding dynamic programming path. In a second aspect, a speech recognition interface is used as a control system for a telephony system.

Apparatus, method and computer readable memory medium for speech recognition using dynamic programming

A system is disclosed for generating a modified data structure defining modified grammar rules for the recognition of a natural language input with pauses in which grammar rules for recognition of a natural language are analysed to identify positions in the grammar rules at which pauses can occur in the natural language. A modified data structure is generated defining the modified grammar rules in dependence upon the analysis. The modified data structure is used to improve the accuracy of recognition of a natural language input with pauses. Where the natural language input is used in conjunction with a second modality input, the analysis is performed to identify the positions of pauses in dependence upon the second modality inputs.

Natural language input method and apparatus

A system has a first machine (to) couplable to a network (N) and capable of carrying out at least one function, a speech data receiver () for receiving speech data representing instructions spoken by a user and specifying a function to be carried out by the first machine and a speech data transmitter () for transmitting the speech data to a speech server () couplable to the network (N). The speech server () has a speech manager () for accessing a speech recognition engine () for performing speech recognition on speech data received over the network to produce recognised speech data, an interpreter () for processing recognised speech data to derive from the speech data commands for causing the first machine to carry out the function specified in the spoken instructions and a command transmitter () for transmitting said commands over the network to the first machine, the first machine having a control command receiver () for receiving control commands over the network (N) from the speech server () and a controller () responsive to the control commands for causing the function specified by the spoken instructions to be carried out.

System, a server for a system and a machine for use in a system

A speech processing apparatus and method are provided for processing an input speech signal to compensate for the effects of noise in the input speech signal. The method and apparatus divide the input speech signal into a plurality of sequential time frames and a set of spectral parameters are extracted for each time frame, which parameters are representative of the input signal during the time frame. The system then processes the input speech by scaling the parameters for each frame in dependence upon a measure of the signal to noise ratio for the input frame. In this way, the effects of additive noise on the input signal can be reduced.

Speech processing apparatus and method measuring signal to noise ratio and scaling speech and noise

A speech recognition method for use in a multimodal input system comprises receiving a multimodal input comprising digitized speech as a first modality input and data in at least one further modality input. Features in the speech and in the data in at least one further modality are identified. The identified features in the speech and in the data are used in the recognition of words by comparing the identified features with states in models for the words. The models have states for the recognition of speech and for words having features in at least one further modality associated with the words, the models also have states for the recognition of events in the further modality or each further modality.

Speech recognition accuracy in a multimodal input system

A method and apparatus is provided for matching a first sequence of patterns representative of a first signal with a second sequence of patterns representative of a second signal. The system uses a plurality of different pruning thresholds (th) to control the propagation of paths which represent possible matchings between a sequence of second signal patterns and a sequence of first signal patterns ending at the current first signal pattern. In particular, the pruning threshold used for a given path during the processing of a current first signal pattern depends upon the position, within the sequence of patterns representing the second signal, of the second signal pattern which is at the end of the given path.

Pattern matching method and apparatus

An apparatus is provided for checking the consistency between two training words which can be used in, for example, a speech recognition or verification system. Two training examples are aligned using a dynamic programming alignment process and an average frame score is calculated from the alignment results together with the worst score in a number of consecutive frames. These values are then compared with similar values obtained from training examples which are known to be consistent to determine if the training examples are consistent.

Speech processing apparatus and method

A speech processing apparatus is provided in which the distribution of energy with frequency within each frame of an input speech signal is determined and any energy components which are less than a masking level determined relative to the maximum energy within the frame are made equal to the masking level.

Speech processing apparatus and method for noise masking

A method and apparatus for matching a first sequence of patterns representative of a first signal with a second sequence of patterns representative of a second signal using a dynamic programming matching technique is described. The second signal patterns which are at the end of a dynamic programming path for a current first signal pattern are listed in an active list,The dynamic programming paths are propagated by processing the second signal patterns on the active list, and a new active list,is generated for the succeeding input pattern. In order to propagate each path, the system determines how many second signal patterns lie within an overlap region in which a comparison has to be made, and processes each path in dependence upon the determined amount of overlap.

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Guildford, United Kingdom

Robert Alexander Keiller