公开(公告)号：US10665241B1

公开(公告)日：2020-05-26

申请号：US16595032

申请日：2019-10-07

Applicant: Verbit Software Ltd.

Inventor： Eric Ariel Shellef ,  Yaakov Kobi Ben Tsvi ,  Iris Getz ,  Tom Livne ,  Roman Himmelreich

IPC: G10L15/22 ,  G10L15/30 ,  G10L15/18 ,  G06F3/0484

Abstract: Being able to rapidly and accurately transcribe long audio recordings, such as same-day transcription of multi-hour legal depositions, is a challenging task. Hybrid transcription, which involves automatic speech recognition (ASR) systems generating initial transcriptions that are then reviewed by human transcribers, can be used to tackle this challenge. However, hybrid transcription may be stymied when the transcribers cannot resolve certain issues in the ASR-generated transcriptions. This disclosure describes rapid resolution of transcription-related inquiries of transcribers. In one embodiment, a computer receives an audio recording that includes speech of multiple people in a room and generates transcriptions of segments of the audio recording utilizing an ASR system. These transcriptions are provided for review of transcribers. The computer receives questions from the transcribers regarding the transcriptions, and transmits the questions to a server in the room, which transmits back answers to the questions by the people in the room.

公开(公告)号：US10607599B1

公开(公告)日：2020-03-31

申请号：US16594809

申请日：2019-10-07

Applicant: Verbit Software Ltd.

Inventor： Eric Ariel Shellef ,  Yaakov Kobi Ben Tsvi ,  Iris Getz ,  Tom Livne ,  Roman Himmelreich ,  Elad Shtilerman

IPC: G10L15/06 ,  G10L15/30 ,  G10L15/26 ,  G10L15/187

Abstract: Described herein are curation of a glossary and its utilization for automatic speech recognition (ASR). In one embodiment, a server receives an audio recording of speech, taken over a period spanning at least two hours. During the first hour, the server generates, utilizing an ASR system, a transcription of a segment of the audio, recorded during the first twenty minutes. The server receives, from a transcriber, a phrase that does not appear in the transcription, but was spoken in the segment, and adds the phrase to a glossary. After the first hour of the period, the server generates, utilizing the ASR system, a second transcription of a second segment of the audio, provides the second transcription and the glossary to a second transcriber, and receives a corrected transcription, in which the second transcriber substituted a second phrase in the second transcription, which was not in the glossary, with the phrase.

公开(公告)号：US10726834B1

公开(公告)日：2020-07-28

申请号：US16594471

申请日：2019-10-07

Applicant: Verbit Software Ltd.

Inventor： Eric Ariel Shellef ,  Yaakov Kobi Ben Tsvi ,  Iris Getz ,  Tom Livne ,  Roman Himmelreich ,  Elad Shtilerman ,  Eli Asor

IPC: G10L15/00 ,  G10L15/187 ,  G10L15/22 ,  G10L15/30 ,  G10L15/26 ,  G10L15/02

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.

公开(公告)号：US10665231B1

公开(公告)日：2020-05-26

申请号：US16595129

申请日：2019-10-07

Applicant: Verbit Software Ltd.

Inventor： Eric Ariel Shellef ,  Yaakov Kobi Ben Tsvi ,  Iris Getz ,  Tom Livne ,  Roman Himmelreich ,  Elisha Yehuda Rosensweig

IPC: G10L15/19 ,  G10L15/22 ,  G10L25/60 ,  G10L15/18 ,  G10L15/30 ,  G10L15/04 ,  G10L15/26 ,  G10L15/20 ,  G10L15/01 ,  G10L15/02 ,  G10L15/06 ,  G06F3/0484

Abstract: Maintaining adequate audio quality is very important for creating fast and accurate transcriptions, especially in a hybrid transcription setting, in which human transcribers review transcriptions generated by automatic speech recognition (ASR) systems. Some embodiments described herein involve detecting low-quality audio intended for transcription. In one embodiment, a server receives an audio recording that includes speech. The server generates feature values based on a segment of the audio recording and utilizes a model to calculate, based on the feature values, a certain value indicative of expected hybrid transcription quality of the segment. The model is generated based on training data that includes feature values generated based on previously recorded segments of audio, and values of transcription-quality metrics generated based on transcriptions of the previously recorded segments, which were generated at least in part by human transcribers. Optionally, an alert is provided responsive to the certain value being below a threshold.