Simba 3.2 is a flagship text-to-speech (TTS) model developed by SpeechifyAI, designed for high-quality, real-time voice synthesis. It is a streaming-native model optimized for a balance of human-like expressiveness and operational efficiency. Following its release, it attained a top position on the independent Artificial Analysis TTS Leaderboard, performing favorably against established models from major AI providers in blind human preference testing.
Technically, Simba 3.2 is engineered to achieve a time-to-first-byte (TTFB) of less than 100 milliseconds, making it particularly suitable for latency-sensitive applications like conversational AI agents and interactive voice assistants. It represents a significant iteration in the SIMBA series, succeeding the Simba 3.0 version with enhancements in prosody, emotional range, and audio consistency. The model aims to produce natural-sounding speech that minimizes the mechanical artifacts often associated with synthetic voices.
The model provides granular control over speech characteristics, including per-voice speaking rates and ADV (Arousal, Dominance, Valence) emotion controls. These parameters allow developers to customize speech delivery to fit various use cases, ranging from professional narrations to emotive digital personas. While the initial release focuses on high-fidelity English output, the underlying architecture is designed to support a wide range of voices and future multilingual expansion.