Automated Transcription Model Adaptation via Statistical Feedback
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Solution Overview
Problem
The creation of locally adaptive audio transcription models for customer service interactions is expensive and time-consuming due to reliance on manual transcriptions.
Innovation Solution
An automated method and system for adapting transcription models by obtaining audio data from multiple files, transcribing them, selecting the best transcription alternatives, calculating statistics, and modifying the models based on these statistics to create an adapted model tailored to specific subjects or regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual transcriptions are used to create locally adaptive models, then transcription accuracy is improved, but cost and time consumption increase
Solution Approach 1:
The system performs preliminary automated transcription and selection of alternative transcriptions before final model creation. By pre-processing the audio data and generating multiple transcription alternatives in advance, the system reduces the time and cost of manual transcription while maintaining accuracy through subsequent automated selection and statistics calculation.
2Measurement precision
If manual transcriptions are used to create locally adaptive models, then transcription accuracy is improved, but cost increases
Solution Approach 1:
The system enables self-service automated model adaptation by allowing the transcription model to automatically improve itself through statistics calculation from selected transcriptions. The system serves its own adaptation needs by automatically generating transcription alternatives, selecting the best ones, calculating statistics, and updating the model without requiring external manual transcription services, thereby reducing cost while maintaining accuracy.
3Productivity
If automated transcription is used, then cost and time are reduced, but transcription accuracy may decrease
Solution Approach 1:
The system implements feedback by calculating statistics from selected transcription alternatives and using these statistics to adapt and improve the transcription model. The automated process generates multiple transcription alternatives, selects the best ones based on statistical analysis, and feeds this information back to update the model, thereby maintaining accuracy while improving productivity through automation.
4Measurement precision
If multiple transcription alternatives are generated and selected, then transcription accuracy is improved, but processing complexity increases
Solution Approach 1:
The system introduces statistics calculation as an intermediary step between generating multiple transcription alternatives and selecting the best transcription. This intermediary process systematically evaluates the alternatives through statistical analysis, making the selection process more manageable and less complex while still achieving high accuracy through data-driven decision making.
Data Source
AI summary
Methods, systems, and computer readable media for automated transcription model adaptation includes obtaining audio data from a plurality of audio files. The audio data is transcribed to produce at least one audio file transcription which represents a plurality of transcription alternatives for each audio file. Speech analytics are applied to each audio file transcription. A best transcription is selected from the plurality of transcription alternatives for each audio file. Statistics from the selected best transcription are calculated. An adapted model is created from the calculated statistics.