To analyze customer sentiment, which property and machine learning API should be utilized?

Analyzing customer sentiment requires understanding the emotional tone behind spoken or written text. The most appropriate choice for this task is to utilize the sentiment score and magnitude provided by the Cloud Natural Language API.

The sentiment score represents the overall sentiment conveyed in the text, quantifying how positive or negative the sentiment is on a scale from -1.0 (very negative) to 1.0 (very positive). The magnitude indicates the strength of that sentiment, regardless of whether it is positive or negative. This means that you can assess not just how a customer feels, but also how strongly they feel about it, which is crucial for accurately gauging customer sentiments.

Other options do not offer the specific capabilities needed for sentiment analysis. For instance, the Speech-to-Text API provides transcripts of spoken text, which is useful for converting audio to text but does not perform sentiment analysis itself. The Vision API assesses images and provides label scores and descriptions, which are unrelated to sentiment in text. Therefore, using the sentiment score and magnitude from the Cloud Natural Language API is the most effective way to analyze customer sentiment accurately.