Your customer service team stores thousands of recorded phone calls in Cloud Storage. They want to extract the spoken words so they can later run sentiment analysis with Natural Language API. Which pre-trained Google Cloud API should they use to create the text transcripts from audio?
The Speech-to-Text API is designed to convert spoken language in audio files into written text. This allows the company to obtain transcripts of the calls, which can then be passed to the Natural Language API for sentiment or keyword analysis. Text-to-Speech performs the opposite conversion (text into audio), Vision API analyzes image content, and Cloud Translation API converts written text between languages-none of these generate text from audio input.
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How does the Speech-to-Text API process audio files?
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What is the difference between the Speech-to-Text API and Text-to-Speech API?
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How does Natural Language API conduct sentiment analysis on transcripts?
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How does Speech-to-Text API convert audio to text?
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What features make the Natural Language API suitable for sentiment analysis?
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Is there a way to process batch audio files with Speech-to-Text API?
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