Abstract: In one embodiment, a method includes receiving first Light Detection and Ranging (LiDAR) data associated with a railroad environment, extracting an asset from the first LiDAR data associated with the railroad environment, and superimposing the asset into a spatial model. The method also includes receiving a field indication associated with a modification to the railroad environment and modifying the spatial model in response to receiving the field indication associated with the modification to the railroad environment. The method further includes receiving second LiDAR data associated with the railroad environment and comparing the second LiDAR data to the modified spatial model.

Abstract: Methods, systems, and related products that provide detection of media content items that are under-locatable by machine voice-driven retrieval of uttered requests for retrieval of the media items. For a given media item, a resolvability value and/or an utterance resolve frequency is calculated by a number of playbacks of the media item by a speech retrieval modality to a total number of playbacks of the media item regardless of retrieval modality. In some examples, the methods, systems and related products also provide for improvement in the locatability of an under-locatable media item by collecting and/or generating one or more pronunciation aliases for the under-locatable item.

Abstract: Methods, systems, and related products that provide detection of media content items that are under-locatable by machine voice-driven retrieval of uttered requests for retrieval of the media items. For a given media item, a resolvability value and/or an utterance resolve frequency is calculated by a number of playbacks of the media item by a speech retrieval modality to a total number of playbacks of the media item regardless of retrieval modality. In some examples, the methods, systems and related products also provide for improvement in the locatability of an under-locatable media item by collecting and/or generating one or more pronunciation aliases for the under-locatable item.

Abstract: In one embodiment, a method includes receiving first Light Detection and Ranging (LiDAR) data associated with a railroad environment, extracting an asset from the first LiDAR data associated with the railroad environment, and superimposing the asset into a spatial model. The method also includes receiving a field indication associated with a modification to the railroad environment and modifying the spatial model in response to receiving the field indication associated with the modification to the railroad environment. The method further includes receiving second LiDAR data associated with the railroad environment and comparing the second LiDAR data to the modified spatial model.

Abstract: In one embodiment, a method includes receiving first Light Detection and Ranging (LiDAR) data associated with a railroad environment, extracting an asset from the first LiDAR data associated with the railroad environment, and superimposing the asset into a spatial model. The method also includes receiving a field indication associated with a modification to the railroad environment and modifying the spatial model in response to receiving the field indication associated with the modification to the railroad environment. The method further includes receiving second LiDAR data associated with the railroad environment and comparing the second LiDAR data to the modified spatial model.

Abstract: Methods, systems, and related products that provide detection of media content items that are under-locatable by machine voice-driven retrieval of uttered requests for retrieval of the media items. For a given media item, a resolvability value and/or an utterance resolve frequency is calculated by a number of playbacks of the media item by a speech retrieval modality to a total number of playbacks of the media item regardless of retrieval modality. In some examples, the methods, systems and related products also provide for improvement in the locatability of an under-locatable media item by collecting and/or generating one or more pronunciation aliases for the under-locatable item.

Abstract: In one embodiment, a method includes receiving first Light Detection and Ranging (LiDAR) data associated with a railroad environment, extracting an asset from the first LiDAR data associated with the railroad environment, and superimposing the asset into a spatial model. The method also includes receiving a field indication associated with a modification to the railroad environment and modifying the spatial model in response to receiving the field indication associated with the modification to the railroad environment. The method further includes receiving second LiDAR data associated with the railroad environment and comparing the second LiDAR data to the modified spatial model.

Abstract: Methods, systems, and related products that provide detection of media content items that are under-locatable by machine voice-driven retrieval of uttered requests for retrieval of the media items. For a given media item, a resolvability value and/or an utterance resolve frequency is calculated by a number of playbacks of the media item by a speech retrieval modality to a total number of playbacks of the media item regardless of retrieval modality. In some examples, the methods, systems and related products also provide for improvement in the locatability of an under-locatable media item by collecting and/or generating one or more pronunciation aliases for the under-locatable item.

Abstract: Methods, systems, and related products that provide detection of media content items that are under-locatable by machine voice-driven retrieval of uttered requests for retrieval of the media items. For a given media item, a resolvability value and/or an utterance resolve frequency is calculated by a number of playbacks of the media item by a speech retrieval modality to a total number of playbacks of the media item regardless of retrieval modality. In some examples, the methods, systems and related products also provide for improvement in the locatability of an under-locatable media item by collecting and/or generating one or more pronunciation aliases for the under-locatable item.