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Speech Recognition
Speech recognition in customer service is used for transcribing and understanding spoken language from customers, facilitating automated responses, efficient call routing, and improving service quality.
Use case examples:
Transcription and Analysis of Customer Interactions
Speech recognition transcribes customer calls and interactions into text format, enabling businesses to analyze customer sentiment, identify trends, and gather insights to improve products, services, and customer experiences.
Voice of the Customer (VoC) Analysis
NLP text analyzers can process customer interactions from various channels such as call transcripts, chat logs, and emails. By extracting insights, trends, and recurring issues, businesses can identify areas for product improvement, enhance customer support, and drive customer loyalty.
Voice-Enabled Virtual Assistants
Speech recognition technology powers voice-enabled virtual assistants that can interact with customers, answer common questions, provide product information, and assist with basic troubleshooting tasks, improving customer service efficiency and accessibility.
Our demo allows you to check the capabilities of modern speech-to-text techniques. Simply record your speech or upload a file and get what was said in digital text format.
Follow these steps to test the demo:
1
Record your speech or upload a recording
2
Click 'Process file' and get the result
Your result will appear here
Remember, the demos presented on our platform are still not the final products. Instead, think of them as the foundation typically laid at the start of a project.
As the project makes progress, models and methods will be refined through iterative training on your datasets, and customized pre-processing and post-processing to meet your business needs.
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