Google Cloud Digital LeaderData and AI with Google CloudMedium
A healthcare provider wants to build a system to automatically transcribe doctor-patient conversations and extract key medical terms, diagnoses, and procedures. They need a service that can handle both audio-to-text conversion and advanced natural language processing. Which combination of Google Cloud AI products should they use?
- ASpeech-to-Text and Natural Language API
- BTranslation AI and AutoML Tables
- CVideo Intelligence API and BigQuery ML
- DDialogflow and Vision AI
Show answer & explanationAnswer & explanation
Correct answer: A. Speech-to-Text and Natural Language API
Speech-to-Text is used to convert spoken language into written text, addressing the transcription requirement. The Natural Language API can then be used to analyze this text to extract entities (medical terms), sentiments, and other linguistic features, fulfilling the natural language processing needs.
Why the other options are wrong
- B. Translation AI is for language translation, and AutoML Tables for structured data ML, not audio or text entity extraction.
- C. Video Intelligence API analyzes video, and BigQuery ML is for ML on structured data in BigQuery, neither for audio transcription or text entity extraction.
- D. Dialogflow is for conversational interfaces, and Vision AI for image analysis, neither fits the audio transcription and text analysis need.
Speech-to-Text API & Natural Language API
A combination of Google Cloud APIs for converting spoken audio into text and then analyzing that text for insights.
- Speech-to-Text: Accurate transcription of audio files.
- Natural Language API: Entity extraction, sentiment analysis, syntax analysis, content classification.
- Commonly used together for processing spoken language data.
Memory trick: Speak to Text, then Natural Language understands.