Encoder-decoder architecture for generating natural language data based on telemetry data
AssigneeHoneywell International Inc.
InventorsRaman Samusevich, Karel Marik, Petr Endel, Marek Sikora
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Abstract
Systems and methods provide techniques for generating natural language data based on telemetry data. In one embodiments, a method includes at least operations configured to receive telemetry data, wherein the telemetry data includes temporal telemetry vectors; process the temporal telemetry vectors using an encoder model in order to generate a feature vector for the telemetry data; and process the feature vector using a decoder model in order to generate the natural language data.
Claims15
A computer-implemented method for predictive inference of natural language data based on telemetry data, the computer-implemented method comprising:
- receiving the telemetry data, wherein the telemetry data comprises a plurality of temporal telemetry vectors;
- processing the plurality of temporal telemetry vectors using an encoder model in order to generate a feature vector for the telemetry data, wherein the encoder model is configured to process each temporal telemetry vector of the plurality of temporal telemetry vectors at a corresponding encoding timestep of a plurality of encoding timesteps associated with the encoder model;
- and
- processing the feature vector using a decoder model in order to generate the natural language data, wherein the natural language data comprises a plurality of natural language tokens, and wherein the decoder model generates each natural language token of the plurality of natural language tokens at a corresponding decoding timestep of a plurality of decoding timesteps associated with the decoder model.
An apparatus for predictive inference of natural language data based on telemetry data, the apparatus comprising at least one processor and at least one memory including program code, the at least one memory and the program code configured to, with the processor, cause the apparatus to at least:
- receive the telemetry data, wherein the telemetry data comprises a plurality of temporal telemetry vectors;
- process the plurality of temporal telemetry vectors using an encoder model in order to generate a feature vector for the telemetry data, wherein the encoder model is configured to process each temporal telemetry vector of the plurality of temporal telemetry vectors at a corresponding encoding timestep of a plurality of encoding timesteps associated with the encoder model;
- and
- process the feature vector using a decoder model in order to generate the natural language data, wherein the natural language data comprises a plurality of natural language tokens, and wherein the decoder model generates each natural language token of the plurality of natural language tokens at a corresponding decoding timestep of a plurality of decoding timesteps associated with the decoder model.
A computer program product for predictive inference of natural language data based on telemetry data, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions configured to:
- receive the telemetry data, wherein the telemetry data comprises a plurality of temporal telemetry vectors;
- process the plurality of temporal telemetry vectors using an encoder model in order to generate a feature vector for the telemetry data, wherein the encoder model is configured to process each temporal telemetry vector of the plurality of temporal telemetry vectors at a corresponding encoding timestep of a plurality of encoding timesteps associated with the encoder model;
- and
- process the feature vector using a decoder model in order to generate the natural language data, wherein the natural language data comprises a plurality of natural language tokens, and wherein the decoder model generates each natural language token of the plurality of natural language tokens at a corresponding decoding timestep of a plurality of decoding timesteps associated with the decoder model.
Dependencies are inferred from the claim text.