Verbit Software Ltd.

Elad Shtilerman

Eric Ariel Shellef

Tom Livne

Yaakov Kobi Ben Tsvi

Iris Getz

Roman Himmelreich

Eli Asor

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

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.

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Aseret, Israel

Elad Shtilerman