A: Hi @107265902650358569492, happy to elaborate.

When we mention “analyzing emotions and voice tone” in Release0, here’s what it means:

1. Source of Analysis

Currently, the emotion/tone analysis is based on text rather than raw audio signals. That means the AI interprets sentiment, style, and inferred emotional state from the words and phrases the user inputs (or from transcribed voice messages).
If you’re working with voice inputs, the voice is transcribed first, and then the same text-based emotional/tone analysis applies.

2. Criteria Evaluated

The system can look for several textual indicators of tone and mood, including:
• Sentiment polarity (positive, negative, neutral)
• Emotional indicators (e.g., excitement, frustration, curiosity, hesitation)
• Vocabulary patterns (formal vs. casual, polite vs. direct)
• Intensity and emphasis (use of caps, punctuation, repetition)
• Shifts over time in a conversation (tone becoming more positive or negative)

While we don’t currently extract rhythm or prosody directly from the voice waveform (like pitch or speed analysis), many of those cues can be indirectly inferred from how the transcript is written e.g., long pauses, abrupt statements, or certain stylistic markers.