Moshi

Definitions

1. Moshi is a real-time speech-native model architecture aimed at low-latency spoken interaction. It is commonly used for voice assistants and conversational speech systems, where teams need predictable behavior under real workloads rather than toy examples. Practitioners pay attention to turn-taking latency, audio quality, and multimodal coordination, because those factors usually determine whether the approach improves quality, latency, reliability, or operating cost in production.

   In plain English: Moshi is an AI concept teams use to train models, guide predictions, or make model behavior more reliable and easier to control in practice.

   Example: "We evaluated Moshi in the new model pipeline because the baseline was plateauing; once it was wired into training and evaluation, quality improved enough to justify rolling it into the next release."

Related Terms

• Lemmatization
• Linear Layer
• Linear Probe
• Linear Regression
• Llama
• Logistic Regression
• Logit
• Long Short-Term Memory