Verbit Software Ltd.

Eli Asor

Eric Ariel Shellef

Tom Livne

Yaakov Kobi Ben Tsvi

Iris Getz

Elad Shtilerman

Elisha Yehuda Rosensweig

Roman Himmelreich

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. The computer then updates the transcription of the audio recording based on the indication and the correct transcription.

Human resolution of repeated phrases in a hybrid transcription system

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.

Human-based accent detection to assist rapid transcription with automatic speech recognition

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.

Early selection of operating parameters for automatic speech recognition based on manually validated transcriptions

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Tel Aviv, Israel

Eli Asor