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Earlybird speech model predicts words 90ms before spoken

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Earlybird, a novel speech recognition model that significantly reduces latency by predicting words before they are fully spoken. Unlike traditional streaming models that output words after completion, Earlybird can predict words up to 90 milliseconds before the speaker finishes them, with a 69% prediction accuracy on audiobooks. This model, with 29 million parameters, also provides confidence scores for words still being spoken and outperforms existing models on various test sets, including the Open ASR Leaderboard. AI

IMPACT Reduces latency in speech recognition, enabling faster responses for voice agents and real-time applications.

RANK_REASON Research paper detailing a new model architecture and performance. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Earlybird speech model predicts words 90ms before spoken

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36 / 100
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Research paper detailing a new model architecture and performance. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Sahil Mahendrakar ·

    Earlybird: Predictive Streaming Speech Recognition in 29M Parameters

    arXiv:2611.14421v1 Announce Type: cross Abstract: Streaming speech recognizers output a word only after the speaker has finished it, typically 90-400 ms later. For a voice agent every millisecond counts: the sooner the words are outputted, the sooner the agent can start a search …

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