Patents by Inventor Kani Chen

Kani Chen has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Enhanced speech-to-text performance with mixed languages
    Patent number: 12749478
    Abstract: Training a mixed language speech recognition model, and speech recognition performed by the model, can be enhanced. Model manager can control training and/or operation of the model. Mixed language data generation manager can generate an enhanced mixed language dataset that can enhance training of the model. Fine tuner can facilitate configuring hyperparameters of the model. Audio-based information and transcript that are representative of the dataset can be applied to the model to facilitate model training. FAL evaluator can determine fidelity, accuracy, and latency of performance of speech recognition on the audio-based information and transcript by the model. Based on such determination, mixed language data generation process and/or hyperparameters can be updated to enhance further training of the model to enhance fidelity, accuracy, and/or latency regarding performance of speech recognition by the model. Model manager can control one or more iterations of model training.
    Type: Grant
    Filed: September 30, 2024
    Date of Patent: September 29, 2026
    Assignee: THE HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY
    Inventors: Peng Xie, Tsz Wai Chan, Xingyuan Liu, Kani Chen, Yang Wang
  • ENHANCED SPEECH-TO-TEXT PERFORMANCE WITH MIXED LANGUAGES
    Publication number: 20250131915
    Abstract: Training a mixed language speech recognition model, and speech recognition performed by the model, can be enhanced. Model manager can control training and/or operation of the model. Mixed language data generation manager can generate an enhanced mixed language dataset that can enhance training of the model. Fine tuner can facilitate configuring hyperparameters of the model. Audio-based information and transcript that are representative of the dataset can be applied to the model to facilitate model training. FAL evaluator can determine fidelity, accuracy, and latency of performance of speech recognition on the audio-based information and transcript by the model. Based on such determination, mixed language data generation process and/or hyperparameters can be updated to enhance further training of the model to enhance fidelity, accuracy, and/or latency regarding performance of speech recognition by the model. Model manager can control one or more iterations of model training.
    Type: Application
    Filed: September 30, 2024
    Publication date: April 24, 2025
    Inventors: Peng Xie, Tsz Wai Chan, Xingyuan Liu, Kani Chen, Yang Wang