Abstract: A method to detect video copying based on content. The method comprises providing a set of reference data elements derived from a set of reference video frames in a reference video stream; providing a set of query data elements derived from a set of query video frames in a query video stream, each of the query data elements having a corresponding query data element identifier; associating with each of the reference data elements a fingerprint selected from among the query data element identifiers; and determining a similarity measure for the query video stream relative to the reference video stream by a comparison of the query data element identifiers to the fingerprints.

Abstract: A method to detect video copying based on content. The method comprises providing a set of reference data elements derived from a set of reference video frames in a reference video stream; providing a set of query data elements derived from a set of query video frames in a query video stream, each of the query data elements having a corresponding query data element identifier; associating with each of the reference data elements a fingerprint selected from among the query data element identifiers; and determining a similarity measure for the query video stream relative to the reference video stream by a comparison of the query data element identifiers to the fingerprints.

Abstract: A data communication terminal, such as a cellular telephone, capable of synthesizing speech. The data communication terminal can establish a communication session with a base station over a transmission facility implementing a voice channel and a data channel. The data communication terminal includes a speech synthesizer engine that receives from the remote entity a signal transmitted over the data channel and that conveys the vocal tract characteristics of the message to be delivered as a spoken announcement. The base station generates the signal containing the vocal tract characteristics from a text-based signal of the message to be synthesized. The invention also extends to a base station that can convert the text based message to be synthesized into a signal containing vocal tract characteristics and that sends the signal to a remote terminal over the data channel.

Abstract: A data communication terminal, such as a cellular telephone, capable of synthesizing speech. The data communication terminal can establish a communication session with a base station over a transmission facility implementing a voice channel and a data channel. The data communication terminal includes a speech synthesizer engine that receives from the remote entity a signal transmitted over the data channel and that conveys the vocal tract characteristics of the message to be delivered as a spoken announcement. The base station generates the signal containing the vocal tract characteristics from a text-based signal of the message to be synthesized. The invention also extends to a base station that can convert the text based message to be synthesized into a signal containing vocal tract characteristics and that sends the signal to a remote terminal over the data channel.

Abstract: A data communication terminal, such as a cellular telephone, capable of synthesizing speech. The data communication terminal can establish a communication session with a base station over a transmission facility implementing a voice channel and a data channel. The data communication terminal includes a speech synthesizer engine that receives from the remote entity a signal transmitted over the data channel and that conveys the vocal tract characteristics of the message to be delivered as a spoken announcement. The base station generates the signal containing the vocal tract characteristics from a text-based signal of the message to be synthesized. The invention also extends to a base station that can convert the text based message to be synthesized into a signal containing vocal tract characteristics and that sends the signal to a remote terminal over the data channel.

Abstract: Comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, is carried out in an order which makes better use of memory. First, the observations in one of the blocks are compared (31), to a subset comprising one or more of the models, to determine a likelihood of a match to each of the one or more models. This step is repeated (33) for models other than those in the subset; and the whole process is repeated (34) for each block.

Abstract: In methods and apparatus for at least partially automating a telephone directory assistance function, directory assistance callers are prompted to speak locality or called entity names associated with desired directory listings. A speech recognition algorithm is applied to speech signals received in response to prompting to determine spoken locality or called entity names. Desired telephone numbers are released to callers, and released telephone numbers are used to confirm or correct at least some of the recognized locality or called entity names. Speech signal representations labelled with the confirmed or corrected names are used as labelled speech tokens to refine prior training of the speech recognition algorithm. The training refinement automatically adjusts for deficiencies in prior training of the speech recognition algorithm and to long term changes in the speech patterns of directory assistance callers served by a particular directory assistance installation.

Abstract: A method of recognizing speech comprises searching a vocabulary of words for a match to an unknown utterance. Words in the vocabulary are represented by concatenated allophone models and the vocabulary is represented as a network. On a first pass of the search, a one-state duration constrained model is used to search the vocabulary network. The one-state model has as its transition probability the maximum observed transitional probability (model distance) of the unknown utterance for the corresponding allophone model. Words having top scores are chosen from the first pass search and, in a second pass of the search, rescored using a full Viterbi trellis with the complete allophone models and model distances. The rescores are sorted to provide a few top choices. Using a second set of speech parameters these few top choices are again rescored. Comparison of the scores using each set of speech parameters determines a recognition choice. Post processing is also possible to further enhance recognition accuracy.

Abstract: In methods and apparatus for at least partially automating a telephone directory assistance function, directory assistance callers are prompted to speak locality or called entity names associated with desired directory listings. A speech recognition algorithm is applied to speech signals received in response to prompting to determine spoken locality or called entity names. Desired telephone numbers are released to callers, and released telephone numbers are used to confirm or correct at least some of the recognized locality or called entity names. Speech signal representations labelled with the confirmed or corrected names are used as labelled speech tokens to refine prior training of the speech recognition algorithm. The training refinement automatically adjusts for deficiencies in prior training of the speech recognition algorithm and to long term changes in the speech patterns of directory assistance callers served by a particular directory assistance installation.

Abstract: A flexible vocabulary speech recognition system is provided for recognizing speech transmitted via the public switched telephone network. The flexible vocabulary recognition (FVR) system is a phoneme based system. The phonemes are modelled as hidden Markov models. The vocabulary is represented as concatenated phoneme models. The phoneme models are trained using Viterbi training enhanced by: substituting the covariance matrix of given phonemes by others, applying energy level thresholds and voiced, unvoiced, silence labelling constraints during Viterbi training. Specific vocabulary members, such as digits, are represented by allophone models. A* searching of the lexical network is facilitated by providing a reduced network which provides estimate scores used to evaluate the recognition path through the lexical network. Joint recognition and rejection of out-of-vocabulary words are provided by using both cepstrum and LSP parameter vectors.

Abstract: In a speech recognizer, for recognizing unknown utterances in isolated-word speech or continuous speech, improved recognition accuracy is obtained by augmenting the usual spectral representation of the unknown utterance with a dynamic component. A corresponding dynamic component is provided in the templates with which the spectral representation of the utterance is compared. In preferred embodiments, the representation is mel-based cepstral and the dynamic components comprise vector differences between pairs of primary cepstra. Preferably the time interval between each pair is about 50 milliseconds. It is also preferable to compute a dynamic perceptual loudness component along with the dynamic parameters.