Customer sentiment analysis: methods, tools, and what voice data adds

Argues effective sentiment analysis requires transcription accuracy below 5% WER, proper speaker identification, and language models robust across accents and code-switching. Voice-only sentiment tools overlook audio indicators like speaking pace, overlapping speech, and vocal intensity, while automated scoring on accurate transcripts enables monitoring of all calls rather than just 2-5%.