Amazon Transcribe is the correct choice because it converts recorded call audio into text so downstream tools can extract entities sentiment and key phrases from the transcripts.

Amazon Transcribe performs automatic speech to text at scale and supports batch and streaming transcription along with speaker identification timestamps and vocabulary tuning to improve accuracy. These transcripts are the required input for NLP services so you can send them to tools that perform entity extraction sentiment analysis and other text analytics.

Amazon Lex is focused on building chatbots and conversational interfaces and it does not provide a service to transcribe recorded audio files into text.

Amazon SageMaker Model Monitor is intended to monitor data and model quality in machine learning deployments and it does not perform audio transcription or text extraction from recordings.

Amazon Comprehend provides NLP capabilities such as entity recognition sentiment detection and key phrase extraction but it operates on text only and therefore requires a speech to text step first so it cannot by itself convert call recordings into transcripts.

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