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All digests tagged Speech Recognition
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Learn how to build a voice agent by integrating Speech-to-Text, LLMs, and Text-to-Speech. We demonstrate using AssemblyAI and LiveKit, including advanced features like tool calling and voice cloning.
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Building a Voice OS requires moving beyond accurate ASR to mastering latency, personalization, and style inference. The talk details using LLMs and RL to structure raw speech into polished, usable communication.
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Voice AI failures are not random bugs, but structural issues. Kim introduces a linguistic framework mapping communication to two channels (listening/speaking) and four interdependent levels: sounds, words, interaction, and mental model.
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The talk details the evolution of voice agents, arguing that achieving full-duplex, natural conversation requires a hybrid architecture: coupling a small S2S interface with a powerful background text LLM.
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Gemini 3.5 Transcribe is an LLM-based transcription model available via Interactions API and Live API, enabling fast, contextually accurate transcribing of multi-speaker recordings.
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Gemini 3.5 Transcribe is an LLM-based transcription model available on the Interactions and Live APIs. It excels at transcribing complex data like email addresses, phone numbers, and multilingual speech.
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