Abstract: A computer-implemented system and method for efficient voice transcription is provided. A verbal message is processed by splitting the verbal message into segments and generating text for each of the segments via automated speech recognition. A confidence score is assigned to each text segment. The text segments are provided to workbenches, in order, staring with the text segment having a lowest confidence score. For at least one text segment provided to the workbench, one of edits to the text segment and manually transcribed text to replace the text segment are received. A threshold is applied to a time for performing the message processing and upon satisfaction of the threshold, the message processing is terminated. A text message is generated for the verbal message based on one of the generated text segment, manual transcription, or edited text segment for each of the text segments in that verbal message.

Abstract: A computer-implemented system and method for transcribing verbal messages is provided. Verbal messages each comprising audio content are received. Automatically recognized text is generated for the audio content of at least one of the verbal messages. A turn-around processing time is applied to the verbal message. The automatically recognized text and verbal message are transferred to a human agent when an expected processing time of the verbal message satisfies the turn-around processing time. At least a portion of the automatically recognized text is replaced with manual transcription from the human agent. The automatically recognized text and manual transcription are provided as a text message.

Abstract: A computer-implemented system and method for transcribing verbal messages is provided. Verbal messages each comprising audio content are received. Automatically recognized text is generated for the audio content of at least one of the verbal messages. A turn-around processing time is applied to the verbal message. The automatically recognized text and verbal message are transferred to a human agent when an expected processing time of the verbal message satisfies the turn-around processing time. At least a portion of the automatically recognized text is replaced with manual transcription from the human agent. The automatically recognized text and manual transcription are provided as a text message.

Abstract: A system and method for efficiently transcribing verbal messages to text is provided. Verbal messages are received and at least one of the verbal messages is divided into segments. Automatically recognized text is determined for each of the segments by performing speech recognition and a confidence rating is assigned to the automatically recognized text for each segment. A threshold is applied to the confidence ratings and those segments with confidence ratings that fall below the threshold are identified. The segments that fall below the threshold are assigned to one or more human agents starting with those segments that have the lowest confidence ratings. Transcription from the human agents is received for the segments assigned to that agent. The transcription is assembled with the automatically recognized text of the segments not assigned to the human agents as a text message for the at least one verbal message.

Abstract: A system and method for efficiently transcribing verbal messages to text is provided. Verbal messages are received and at least one of the verbal messages is divided into segments. Automatically recognized text is determined for each of the segments by performing speech recognition and a confidence rating is assigned to the automatically recognized text for each segment. A threshold is applied to the confidence ratings and those segments with confidence ratings that fall below the threshold are identified. The segments that fall below the threshold are assigned to one or more human agents starting with those segments that have the lowest confidence ratings. Transcription from the human agents is received for the segments assigned to that agent. The transcription is assembled with the automatically recognized text of the segments not assigned to the human agents as a text message for the at least one verbal message.

Abstract: A system and method for efficiently transcribing verbal messages transmitted over the Internet (or other network) into text. The verbal messages are initially checked to ensure that they are in a valid format and include a return network address, and if so, are processed either as whole verbal messages or split into segments. These whole verbal messages and segments are processed by an automated speech recognition (ASR) program, which produces automatically recognized text. The automatically recognized text messages or segments are assigned to selected workbenches for manual editing and transcription, producing edited text. The segments of edited text are reassembled to produce whole edited text messages, undergo post processing to correct minor errors and output as an email, an SMS message, a file, or an input to a program. The automatically recognized text and manual edits thereof are returned as feedback to the ASR program to improve its accuracy.

Abstract: A system and method for efficiently transcribing verbal messages transmitted over the Internet (or other network) into text. The verbal messages are initially checked to ensure that they are in a valid format and include a return network address, and if so, are processed either as whole verbal messages or split into segments. These whole verbal messages and segments are processed by an automated speech recognition (ASR) program, which produces automatically recognized text. The automatically recognized text messages or segments are assigned to selected workbenches for manual editing and transcription, producing edited text. The segments of edited text are reassembled to produce whole edited text messages, undergo post processing to correct minor errors and output as an email, an SMS message, a file, or an input to a program. The automatically recognized text and manual edits thereof are returned as feedback to the ASR program to improve its accuracy.