It’s important to keep up with the quickly changing voice technology landscape. Here are the top ten terms to know.

1. Valence - Measures the positivity or negativity in a speaker's tone, crucial for determining emotional states.

2. Tonal Analysis - Examines vocal qualities like pitch and rhythm to understand emotions, intentions, and stress levels.

3. Voice AI - Encompasses technologies that process and understand human speech, including emotional content.

4. Emotion Detection - Identifies human emotions through vocal patterns, essential for understanding a speaker's emotional state.

5. Speech Recognition - Enables machines to understand and process human speech, foundational in voice AI systems.

6. Conversational AI - Uses AI to enable machines to engage in human-like conversations, integrating NLP and sentiment analysis.

7. Sentiment Analysis - Assesses emotional tone during conversations from the words said.

8. Affective Computing - Involves creating systems that recognize, interpret, and respond to human emotions, enhancing AI interactions.

9. Voice Biometrics - Uses unique vocal characteristics to verify identity, important for security in voice interactions.

10. Prosody - Rhythm, stress, and intonation in speech to that conveys emotional nuance.