Paralanguage in voice AI: a complete guide to paralinguistic cues

Paralinguistic cues are vocal signals that convey meaning beyond words, including prosody, voice quality, disfluency, timing and silence, and non-speech vocalizations such as laughter or sighs. Production transcription systems currently support timing measurements through word timestamps and speaker diarization, while some providers can retain filler words like “uh” and “um,” but they generally do not label repairs, false starts, or other disfluencies without post-processing. Prosody and voice-quality features, including pitch, loudness, breathiness, jitter, shimmer, and harmonics-to-noise ratio, can be measured from raw audio using tools such as openSMILE and Praat, but are not broadly returned by transcription APIs and lack consistent mappings from acoustic values to perceptual labels. Non-speech vocalizations have the weakest commercial support, with AssemblyAI documenting laughter tags but no major provider offering documented sigh or crying detection. The guidance recommends preserving audio alongside timestamped, diarized transcripts, since deleting recordings permanently prevents later extraction of prosodic and voice-quality information.

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