Abstract: Automatic speech recognition (ASR) processing including a feedback configuration to allow for improved disambiguation between ASR hypotheses. After ASR processing of an incoming utterance where the ASR outputs an N-best list including multiple hypotheses, the multiple hypotheses are passed downstream for further processing. The downstream further processing may include natural language understanding (NLU) or other processing to determine a command result for each hypothesis. The command results are compared to determine if any hypotheses of the N-best list would yield similar command results. If so, the hypothesis(es) with similar results are removed from the N-best list so that only one hypothesis of the similar results remains in the N-best list. The remaining non-similar hypotheses are sent for disambiguation, or, if only one hypothesis remains, it is sent for execution.

Abstract: Automatic speech recognition (ASR) processing including a two-stage configuration. After ASR processing of an incoming utterance where the ASR outputs an N-best list including multiple hypotheses, a first stage determines whether to execute a command associated with one of the hypotheses or whether to output some of the hypotheses of the N-best list for disambiguation. A second stage determines what hypotheses should be included in the disambiguation choices. A first machine learning model is used at the first stage and a second machine learning model is used at the second stage. The multi-stage configuration allows for reduced speech processing errors as well as a reduced number of utterances sent for disambiguation, which thus improves the user experience.

Abstract: Techniques are described for documenting the positions of items in a room, such as in rooms that are configured for testing automated systems that perform position-related functions. A non-contact measuring tool may be placed at different reference positions within the room. At each position, measurements are made to the room corners and to items of interest within the room. Based on this information, coordinates of the reference positions are calculated. Coordinates of the items are calculated based on the determined coordinates of the reference positions.

Abstract: Features are disclosed for detecting an event in input data using a cascade-based detection system. Detection of the event may be triggered at any stage of the cascade, and subsequent stages of the cascade are not reached in such cases. Individual stages of the cascade may be associated with detection thresholds for use in triggering detection of the event. The sequence of stages may be selected based on some observed or desired operational characteristic, such as latency or operational cost. In addition, the cascade may be modified or updated based on data received from client devices. The data may relate to measurements and determinations made during real-world use of the cascade to detect events in input data.

Abstract: A multi-orientation text detection method and associated system is disclosed that utilizes orientation-variant glyph features to determine a text line in an image regardless of an orientation of the text line. Glyph features are determined for each glyph in an image with respect to a neighboring glyph. The glyph features are provided to a learned classifier that outputs a glyph pair score for each neighboring glyph pair. Each glyph pair score indicates a likelihood that the corresponding pair of neighboring glyphs form part of a same text line. The glyph pair scores are used to identify candidate text lines, which are then ranked to select a final set of text lines in the image.