Which solution will meet these requirements with the LEAST operational overhead?
Use Amazon Polly. Build custom lexicons for the product names and abbreviations. Use the StartSpeechSynthesisTask API operation for each section of the product manual.
Use Amazon Polly. Build custom Speech Synthesis Markup Language (SSML) for the product names and abbreviations. Use the StartDocumentTextDetection API operation for each section of the product manual.
Use Amazon Textract. Build custom Speech Synthesis Markup Language (SSML) for the product names and abbreviations. Use the StartDocumentTextDetection API operation for each section of the product manual.
Use Amazon Textract. Build custom lexicons for the product names and abbreviations. Use the StartTranscriptionJob API operation for each section of the product manual.
Explanations:
Amazon Polly allows for the use of custom lexicons, which can help pronounce product names and abbreviations accurately. Using the StartSpeechSynthesisTask API for each section efficiently synthesizes speech with minimal overhead, as it directly supports audio generation from text.
While Amazon Polly supports SSML for pronunciation customization, the StartDocumentTextDetection API is not suitable for synthesizing speech; it is meant for text detection in documents, not audio generation.
Amazon Textract is primarily for text extraction from documents, not for speech synthesis. While SSML can be used, the process of using Textract introduces unnecessary complexity and overhead.
Amazon Textract is not designed for speech synthesis, and the StartTranscriptionJob API is related to transcribing audio, not generating audio from text. This option would not meet the requirement for creating an audio version of a product manual.
I deduce that the answer is:
Use Amazon Polly. Build custom lexicons for the product names and abbreviations. Use the StartSpeechSynthesisTask API operation for each section of the product manual.