Speech isn’t just words.
It includes emotion, accent, tone, and identity – all mixed together.
Traditional audio tokens try to capture everything.
That makes them heavy, complex, and inefficient for language models.
For example:
Imagine someone says:
“I really need this done today,”
in an urgent tone.
Raw speech contains the words, pitch, pauses, emotion, accent, and background noise.
But for understanding the message, the AI mainly needs:
→ the words
→ the urgency
Enters FocalCodec
It compresses speech into very small tokens that keep the meaning and clarity, without unnecessary details.
FocalCodec keeps these essential parts and removes unnecessary details, so the model understands what is being said without processing everything else.
This is what moves AI from listening to actually understanding humans.
Read more about FocalCodec here - https://lnkd.in/gzRwwu5y
speech-tokens-spoken.html
