Abstract: An apparatus and a method for constructing a multilingual acoustic model, and a computer readable recording medium are provided. The method for constructing a multilingual acoustic model includes dividing an input feature into a common language portion and a distinctive language portion, acquiring a tandem feature by training the divided common language portion and distinctive language portion using a neural network to estimate and remove correlation between phonemes, dividing parameters of an initial acoustic model constructed using the tandem feature into common language parameters and distinctive language parameters, adapting the common language parameters using data of a training language, adapting the distinctive language parameters using data of a target language, and constructing an acoustic model for the target language using the adapted common language parameters and the adapted distinctive language parameters.

Abstract: An apparatus and a method for constructing a multilingual acoustic model, and a computer readable recording medium are provided. The method for constructing a multilingual acoustic model includes dividing an input feature into a common language portion and a distinctive language portion, acquiring a tandem feature by training the divided common language portion and distinctive language portion using a neural network to estimate and remove correlation between phonemes, dividing parameters of an initial acoustic model constructed using the tandem feature into common language parameters and distinctive language parameters, adapting the common language parameters using data of a training language, adapting the distinctive language parameters using data of a target language, and constructing an acoustic model for the target language using the adapted common language parameters and the adapted distinctive language parameters.

Abstract: A dynamic programming technique is provided for matching two sequences of phonemes both of which may be generated from text or speech. The scoring of the dynamic programming matching technique uses phoneme confusion scores, phoneme insertion scores and phoneme deletion scores which are obtained in advance in a training session and, if appropriate, confidence data generated by a recognition system if the sequences are generated from speech.

Abstract: A system is provided for matching two or more sequences of phonemes both or all of which may be generated from text or speech. A dynamic programming matching technique is preferably used having constraints which depend upon whether or not the two sequences are generated from text or speech and in which the scoring of the dynamic programming paths is weighted by phoneme confusion scores, phoneme insertion scores and phoneme deletion scores where appropriate.

Abstract: A data structure is provided for annotating data files within a database. The annotation data comprises a phoneme and word lattice which allows the quick and efficient searching of data files within the database in response to a user's input query. The structure of the annotation data is such that it allows the input query to be made by voice and can be used for annotating various kinds of data files, such as audio data files, video data files, multimedia data files etc. The annotation data may be generated from the data files themselves or may be input by the user either from a voiced input or from a typed input.

Abstract: A data structure is provided for annotating data files within a database. The annotation data comprises a phoneme and word lattice which allows the quick and efficient searching of data files within the database, in response to a user's input query for desired information. The phoneme and word lattice comprises a plurality of time-ordered nodes, and a plurality of links extending between the nodes. Each link has a phoneme or word associated with it. The nodes are arranged in a sequence of time-ordered blocks such that further data can be conveniently added to the lattice.

Abstract: A dynamic programming technique is provided for matching two sequences of phonemes both of which may be generated from text or speech. The scoring of the dynamic programming matching technique uses phoneme confusion scores, phoneme insertion scores and phoneme deletion scores which are obtained in advance in a training session and, if appropriate, confidence data generated by a recognition system if the sequences are generated from speech.

Abstract: A system is provided for determining a sequence of sub-word units representative of at least two words output by a word recognition unit in response to an input word to be recognized. In a preferred embodiment, the word alternatives output by the recognition unit are converted into sequences of phonemes. An optimum alignment between these sequences is then determined using a dynamic programming alignment technique. The sequence of phonemes representative of the input sequences is then determined using this optimum alignment.

Abstract: The data structure is used in accessing a plurality of data files. The data stucture comprises a plurality of annotation storage areas adapted to correspond with the data files, each annotation storage area containing an annotation an annotation representing a time sequential signal and each annotation storage area comprising a plurality of block storage areas each containing phoneme and word data forming a respective temporal block of the annotation and each block having an associated time index identifying a timing of the block within the corresponding annotation. Each block storage area includes a plurality of node storage areas, each asociated with a node which represents a point in time at which a word and/or phoneme begins or ends within the corresponding annotation, and each node storage area having a time offset storage area containing a time offset defining the point in time represented by the node relative to the time index associated with the corresponding block.

Abstract: A system is provided for comparing an input query with a number of stored annotations to identify information to be retrieved from a database. The comparison technique divides the input query into a number of fixed-size fragments and identifies how many times each of the fragments occurs within each annotation using a dynamic programming matching technique. The frequencies of occurrence of the fragments in both the query and the annotation are then compared to provide a measure of the similarity between the query and the annotation. The information to be retrieved is then determined from the similarity measures obtained for all the annotations.

Abstract: An indexing apparatus and method are described for use in identifying portions of data in a database for comparison with a query. In an embodiment, the index includes a key which comprises a sequence of phoneme classifications derived from the input query by classifying each of the phonemes in the input query with a number of phoneme classes, with the phonemes in each class being defined as those that are confusable with the other phonemes in the same class.

Abstract: A system is provided for decoding one or more sequences of sub-word units output by a speech recognition system into one or more representative words. The system uses a dynamic programming technique to align the sequence of sub-word units output by the recognition system with a number of dictionary sub-word unit sequences representative of dictionary words to identify the most likely word or words corresponding to the spoken input.

Abstract: A data structure is provided for annotating data files within a database. The annotation data comprises a phoneme and word lattice which allows the quick and efficient searching of data files within the database, in response to a user's input query for desired information. The phoneme and word lattice comprises a plurality of time-ordered nodes, and a plurality of links extending between the nodes. Each link has a phoneme or word associated with it. The nodes are arranged in a sequence of time-ordered blocks such that further data can be conveniently added to the lattice.

Abstract: A system is provided for decoding one or more sequences of sub-word units output by a speech recognition system into one or more representative words. The system uses a dynamic programming technique to align the sequence of sub-word units output by the recognition system with a number of dictionary sub-word unit sequences representative of dictionary words to identify the most likely word or words corresponding to the spoken input.

Abstract: A data structure is provided for annotating data files within a database. The annotation data comprises a phoneme and word lattice which allows the quick and efficient searching of data files within the database in response to a user's input query. The structure of the annotation data is such that it allows the input query to be made by voice and can be used for annotating various kinds of data files, such as audio data files, video data files, multimedia data files etc. The annotation data may be generated from the data files themselves or may be input by the user either from a voiced input or from a typed input.

Abstract: An indexing apparatus and method are described for use in identifying portions of data in a database for comparison with a query. In an embodiment, the index includes a key which comprises a sequence of phoneme classifications derived from the input query by classifying each of the phonemes in the input query with a number of phoneme classes, with the phonemes in each class being defined as those that are confusable with the other phonemes in the same class.

Abstract: A system is provided for determining a sequence of sub-word units representative of at least two words output by a word recognition unit in response to an input word to be recognized. In a preferred embodiment, the word alternatives output by the recognition unit are converted into sequences of phonemes. An optimum alignment between these sequences is then determined using a dynamic programming alignment technique. The sequence of phonemes representative of the input sequences is then determined using this optimum alignment.