What are end-to-end speech models?
End-to-End Speech Models are simplified architectures that map raw audio directly to a useful output (text, intent, or even synthesized speech) without a chain of separate components.
What is an example of an end-to-end speech model?
Whisper is an end-to-end ASR model that goes from audio to text in a single neural network. Moshi and GPT Realtime are end-to-end speech-to-speech models that go straight from input audio to output audio, skipping the traditional ASR-to-LLM-to-TTS pipeline entirely.
How do end-to-end speech models work?
A single large neural network is trained on massive datasets to jointly learn acoustic features, language structure, and output generation. Raw audio enters, the target output emerges directly.
How does ai-coustics help end-to-end speech models?
End-to-end models still benefit from clean input. Our Quail family enhances audio before it reaches speech-to-speech agents or any other end-to-end system and preserves the acoustic cues these models were trained to understand while removing the noise that degrades them in production.
