Many AWS customers have been successfully using Amazon Transcribe to accurately, efficiently, and automatically convert their customer audio conversations to text, and extract actionable insights from them. These insights can help you continuously enhance the processes and products that directly improve the quality and experience for your customers.
In many countries, such as India, English is not the primary language of communication. Indian customer conversations contain regional languages like Hindi, with English words and phrases spoken randomly throughout the calls. In the source media files, there can be proper nouns, domain-specific acronyms, words, or phrases that the default Amazon Transcribe model isn’t aware of. Transcriptions for such media files can have inaccurate spellings for those words.
In this post, we demonstrate how you can provide more information to Amazon Transcribe with custom vocabularies to update the way Amazon Transcribe handles transcription of your audio files with business-specific terminology. We show

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