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One speech-to-text solution that enables fine-tuning using customer data is Google Cloud Speech-to-Text. This solution allows customers to upload their own audio data to improve the accuracy of the transcription model. The advantage of fine-tuning using customer data is that it can improve the accuracy of the transcription for specific industries or use cases. For example, a customer in the medical industry may have specific terminology that is not recognized by the general model, but by fine-tuning with their own data, they can improve the accuracy of the transcription for their specific needs. The customer who would benefit from fine-tuning are those who have specific language or terminology that is not recognized by the general model. By fine-tuning with their own data, they can improve the accuracy of the transcription for their specific needs. Both the customer's model and the general model can be improved by using the customer's data. The customer's data is used to improve the accuracy of the transcription for their specific needs, but it can also be used to improve the general model for all users. Overall, fine-tuning using customer data is a powerful tool for improving the accuracy of speech-to-text transcription. It allows customers to tailor the transcription to their specific needs and improve the overall accuracy of the model for all users.