Abstract: A synthetic training data item comprising a first sequence of symbols that represent a synthetic sentence output by a simulator is received. The synthetic training data item is processed using a machine learning model, which outputs a second sequence of symbols that represent the synthetic sentence. The synthetic training data item is modified by replacing the first sequence of symbols with the second sequence of symbols. A statistically significant mismatch exists between the first sequence of symbols and a third sequence of symbols that would be output by an acoustic model that processes a set of acoustic features that represent an utterance of the synthetic sentence, and no statistically significant mismatch exists between the second sequence of symbols and the third sequence of symbols. The modified synthetic training data item may be used to train a second machine learning model that processes data output by the acoustic model.

Abstract: A synthetic training data item comprising a first sequence of symbols that represent a synthetic sentence output by a simulator is received. The synthetic training data item is processed using a machine learning model, which outputs a second sequence of symbols that represent the synthetic sentence. The synthetic training data item is modified by replacing the first sequence of symbols with the second sequence of symbols. A statistically significant mismatch exists between the first sequence of symbols and a third sequence of symbols that would be output by an acoustic model that processes a set of acoustic features that represent an utterance of the synthetic sentence, and no statistically significant mismatch exists between the second sequence of symbols and the third sequence of symbols. The modified synthetic training data item may be used to train a second machine learning model that processes data output by the acoustic model.

Abstract: In one embodiment synthetic training data items are generated, each comprising a) a textual representation of a synthetic sentence and b) one or more transcodes of the synthetic sentence comprising one or more actions and one or more entities associated with the one or more actions. For each synthetic training data item, the textual representation of the synthetic sentence is converted into a sequence of phonemes that represent the synthetic sentence. A first machine learning model is then trained as a transcoder that determines transcodes comprising actions and associated entities from sequences of phonemes, wherein the training is performed using a first training dataset comprising the plurality of synthetic training data items that comprise a) sequences phonemes that represent synthetic sentences and b) transcodes of the synthetic sentences. The transcoder may be used in a conversational agent.

Abstract: A virtual mall consists of a graphical user interface having a web page with graphical image that represents the physical structure of a mall. Various sub-regions in the graphical image represent retail stores. The stores are hypertext linked to retail web pages which allow the user to shop for items in much the same way as shopping in a mall. Various icons on the web page allow the user to move form store to store, as well as to various levels of the mall. There are also sub-regions for information, news and magazine subscriptions as well as any other features or services that may be found in malls.

Abstract: In a multipoint data communications system in which a central processing unit communicates with a plurality of remote terminals over a shared two-way communications facility, an automatic fault isolation circuit is provided to monitor energy levels originating at the several remote terminals. One or more energy level thresholds are incorporated into bridging locations through which incoming and outgoing address and message signals are distributed to, and collected from, remote terminals by way of the shared facility for the purposes of detecting noise buildups and isolating trouble conditions automatically without human intervention.