Abstract:
A system, article, and method of automatic speech recognition with highly efficient decoding is accomplished by frequent beam width adjustment.
Abstract:
A computer-implemented method of speech recognition comprises forming a weighted finite state transducer (WFST) having nodes associated with states and interconnected by arcs, and to identify at least one word or word sequence hypothesis, identifying multiple sub-graphs on the WFST, each sub-graph having the same arrangement of multiple states and at least one arc, and propagating tokens in parallel through the sub-graphs, where each sub-graph is stored as a supertoken each having an array of tokens.
Abstract:
Methods, apparatus, systems and articles of manufacture for recognizing speech are disclosed. An example system includes one or more processors to execute instructions to: identify a plurality of phonemes in a speech signal; perform a comparison of a subset of the phonemes to a phonetic string, the phonetic string representative of at least a portion of a wake up phrase; determine if one or more of the phonemes of the subset correspond to the wake up phrase based on the comparison; and generate a hypothesis of a command included in the speech signal by excluding the wake up phrase when one or more of the phonemes of the subset correspond to the wake up phrase or a portion of the wake up phrase.
Abstract:
A system, article, and method of automatic speech recognition with highly efficient decoding is accomplished by frequent beam width adjustment.
Abstract:
A method in a computing device for decoding a weighted finite state transducer (WFST) for automatic speech recognition is described. The method includes sorting a set of one or more WFST arcs based on their arc weight in ascending order. The method further includes iterating through each arc in the sorted set of arcs according to the ascending order until the score of the generated token corresponding to an arc exceeds a score threshold. The method further includes discarding any remaining arcs in the set of arcs that have yet to be considered.
Abstract:
A method in a computing device for decoding a weighted finite state transducer (WFST) for automatic speech recognition is described. The method includes sorting a set of one or more WFST arcs based on their arc weight in ascending order. The method further includes iterating through each arc in the sorted set of arcs according to the ascending order until the score of the generated token corresponding to an arc exceeds a score threshold. The method further includes discarding any remaining arcs in the set of arcs that have yet to be considered.
Abstract:
A mechanism is described for facilitating continuous topic detection and adaption in audio environments, according to one embodiment. A method of embodiments, as described herein, includes detecting a term relating to a topic in an audio input received from one or more microphones of the computing device including a voice-enabled device; analyzing the term based on the topic to determine an action to be performed by the computing device; and triggering an event to facilitate the computing device to perform the action consistent with the term and the topic.