Patents by Inventor Eli Asor

Eli Asor 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).

  • Patent number: 11158322
    Abstract: When transcribing audio recordings, such as legal depositions, phrases may be repeated throughout the recordings, but these repeated phrases get transcribed incorrectly by an automatic speech recognition (ASR) system. In order to assist a transcriber to correctly resolve such phrases, some embodiments described herein involve a computer that receives an audio recording that includes speech, generates a transcription of the audio recording utilizing an ASR system, and clusters segments of the audio recording into clusters of similar utterances. The computer provides a transcriber with certain segments of the audio recording, which include similar utterances belonging to a certain cluster, along with transcriptions of the certain segments. The computer receives from the transcriber: an indication of which of the certain segments include repetitions of a phrase, and a correct transcription of the phrase.
    Type: Grant
    Filed: October 7, 2019
    Date of Patent: October 26, 2021
    Assignee: Verbit Software Ltd.
    Inventors: Eric Ariel Shellef, Yaakov Kobi Ben Tsvi, Iris Getz, Tom Livne, Eli Asor, Elisha Yehuda Rosensweig
  • Publication number: 20210074272
    Abstract: When transcribing audio recordings, such as legal depositions, phrases may be repeated throughout the recordings, but these repeated phrases get transcribed incorrectly by an automatic speech recognition (ASR) system. In order to assist a transcriber to correctly resolve such phrases, some embodiments described herein involve a computer that receives an audio recording that includes speech, generates a transcription of the audio recording utilizing an ASR system, and clusters segments of the audio recording into clusters of similar utterances. The computer provides a transcriber with certain segments of the audio recording, which include similar utterances belonging to a certain cluster, along with transcriptions of the certain segments. The computer receives from the transcriber: an indication of which of the certain segments include repetitions of a phrase, and a correct transcription of the phrase.
    Type: Application
    Filed: October 7, 2019
    Publication date: March 11, 2021
    Applicant: Verbit Software Ltd.
    Inventors: Eric Ariel Shellef, Yaakov Kobi Ben Tsvi, Iris Getz, Tom Livne, Eli Asor, Elisha Yehuda Rosensweig
  • Publication number: 20210074294
    Abstract: When transcribing an audio recording, certain phrases may be difficult to resolve, especially if they involve names and/or infrequently used terms. However, often such phrases may be repeated multiple times throughout the audio recording. Embodiments described herein interact with a transcriber to resolve such cases of repeated phrases. In one embodiment, a computer plays segments of an audio recording to the transcriber, and at least some of the segments include an utterance of a phrase. The computer also presents, to the transcriber, transcriptions of the segments, and at least some of the transcriptions do not include a correct transcription of the phrase. The computer receives from the transcriber an indication of which of the segments include an utterance of the phrase and the correct transcription of the phrase, and then updates a transcription of the audio recording accordingly.
    Type: Application
    Filed: October 7, 2019
    Publication date: March 11, 2021
    Applicant: Verbit Software Ltd.
    Inventors: Eric Ariel Shellef, Yaakov Kobi Ben Tsvi, Iris Getz, Tom Livne, Eli Asor, Elisha Yehuda Rosensweig
  • Patent number: 10726834
    Abstract: Knowing what accent is spoken can assist automatic speech recondition (ASR) systems to more accurately transcribe audio. In one embodiment, a system includes a frontend server configured to transmit, to a backend server, an audio recording that includes speech of one or more people in a room over a period spanning at least two hours. At sonic time during the first hour of the period, the backend server provides a transcriber with a certain segment of the audio recording, and receives, from the transcriber, after the transcriber listened to a certain segment, an indication indicative of an accent of a person who spoke in the certain segment. The backend server then provides the indication to an ASR system to be utilized to generate a transcription of an additional portion of the audio recording, which was recorded after the first twenty minutes of the period.
    Type: Grant
    Filed: October 7, 2019
    Date of Patent: July 28, 2020
    Assignee: Verbit Software Ltd.
    Inventors: Eric Ariel Shellef, Yaakov Kobi Ben Tsvi, Iris Getz, Tom Livne, Roman Himmelreich, Elad Shtilerman, Eli Asor
  • Patent number: 10614810
    Abstract: Early selection of operating parameters for improving accuracy of transcriptions generated by automatic speech recognition (ASR) systems. In one embodiment, a server receives an audio recording that includes speech, taken over a period spanning at least two hours. During the first hour, the server receives a ground truth transcription of a certain segment of the audio recording, created by a transcriber after listening to the certain segment. The server operates an ASR system a plurality of times, using a plurality of sets of operating parameters, to generate a plurality of respective transcriptions of the certain segment. The server evaluates accuracies of the plurality of transcriptions with respect to the ground truth transcription, and selects an optimal set of operating parameters. The server may then apply the optimal set of operating parameters to transcribe additional segments of the audio recording utilizing the ASR system.
    Type: Grant
    Filed: October 7, 2019
    Date of Patent: April 7, 2020
    Assignee: Verbit Software Ltd.
    Inventors: Eric Ariel Shellef, Yaakov Kobi Ben Tsvi, Iris Getz, Tom Livne, Eli Asor, Elad Shtilerman