Earlybird predicts spoken words before they end in 29M parameters
On LibriSpeech test-clean the median word is correct 90 ms early, and 69% of words are right before they end.
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On LibriSpeech test-clean the median word is correct 90 ms early, and 69% of words are right before they end.
An ensemble of seven LoRA systems reached 22.17% normalized word error rate on elderly rural Spanish speech.
R2T2 maintains stable prefixes in real-time transcription without modifying earlier outputs while open-sourced by Netease Youdao
39,000-hour GigaSpeech 3 corpus covers five Arabic dialects and reduces WER by 16.6% relative to prior systems.
Open-source 31.6M-parameter Turkish speech-to-text model outperforms Whisper base on FLEURS and Common Voice tests.
The fine-tuned Turkish GPT-2 beats a multilingual detector, but ties a zero-shot model on unseen speakers.
On Krisp's 265-recording set it reaches 4.95% WER versus 23.21% unprocessed, with 24 ms latency.

The open model transcribes 40 languages while activating about 4 billion of its 30 billion parameters.
The announcement covers open models for speech recognition and decisions on Apple platforms, with no further details available.
Nvidia says the 30-billion-parameter model keeps about 4 billion active and tops open-weight English ASR models.
In banking audio, GRPO cut WER 29.3% to 56.2% relative to SFT and copied 27% of teacher errors.
The Hugging Face post title says the model transcribes, translates, and attributes speech more accurately and faster.
The family keeps 30 languages and 16 Chinese dialects, with file, streaming, and interactive variants.
The set holds about 9 hours of Bemba and 18 hours of Nyanja from 80 and 127 speakers.
TII released Falcon-ASR, a 1.6B Arabic speech model reporting 20.92% average WER; weights are not public.
Oído runs open-vocabulary English speech recognition on a $5 ESP32-S3 without a neural accelerator.
TII introduced Falcon ASR, a speech-recognition release in the Falcon model family.
Fermion Research released Phonon-2, a 164 MB English speech model averaging 5.21% word error.
Pruned CTC restricts alignment computation to target tokens and blank, cutting ASR training memory 5.1x for 180K-vocabulary LLMs with minimal accuracy loss.
Token-level wildcard paths in CTC cut ASR word error by tolerating localized transcript ambiguity.
Edge0 released Audio8-ASR-Infinite, a bilingual streaming speech model with constant-memory unlimited transcription.
IBM details Granite 5.0 TurboCTC, a 470M-parameter Conformer-based English ASR model on the Open ASR speed-accuracy Pareto frontier, released on Hugging Face.

Iceland-based startup Treble raised an $18 million Series A extension to expand its acoustic simulation and synthetic data platform for voice AI companies.

Google says its AI now spans 300+ languages reaching 7 billion people, unveiling Gemini 3.5 Transcribe, Live Translate, and TranslateGemma models.
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