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Topic

Automatic speech recognition

Technology that converts spoken audio into text, used in transcription, voice assistants and conversational AI, spanning many languages and accents.

Current stories

buildOne report1 publisher

IBM says Granite Switch 4.1 fits chat, safety screening and speech in one base model's VRAM

IBM says its Granite Switch 4.1 8B and 30B models run chat, a decision adapter, a guardian adapter and speech recognition in about one base model's VRAM. The memory claim is IBM's own, so any GPU saving depends on what a team serves today.

Reality

Evidence25
Adoption
Not scored
Hype gap+30
Incentives70
Confidence55
buildOne report1 publisher

Interfaze's open-weight interfaze-1-lite attaches confidence scores and bounding boxes to extracted data

Interfaze released interfaze-1-lite, an Apache 2.0 open-weight model for OCR and speech that returns confidence scores and bounding boxes with its answers. Teams can send doubtful rows to a reviewer once they have tested how the scores behave on their own documents.

Publishers:runtimewire.com

Reality

Evidence40
Adoption
Not scored
Hype gap+15
Incentives70
Confidence45
buildConfirmed7 publishers

Microsoft's MAI speech lineup documents real-time use only on the voice-output side

Microsoft's MAI-Transcribe-2 covers 60 languages with speaker labels and word timestamps, though streaming is not among its documented features. Live voice products get a fast model for replies and still need another way to hear the caller.

Perspective Coverage

8 publishers
Builder
Builder 53%
Operator
Operator 30%
Investor
Investor 17%

Reality

Evidence35
Adoption15
Hype gap−35
Incentives65
Confidence70
buildOne report1 publisher

David AI's benchmark finds speech systems 25 points apart on Indic conversation

David AI's 21-language benchmark found speech systems' error rates spread an average of 25.4 points in five Indic languages, against 3.7 in the tightest five. In those languages, choosing a system is a 25-point decision that an English score can make look like a close call.

Publishers:runtimewire.com

Reality

Evidence45
Adoption
Not scored
Hype gap+10
Incentives60
Confidence50
productConfirmed3 publishers

Modulate raises $25 million to sell voice-agent builders a separate audio-analysis layer

Modulate raised $25 million to put models that analyze raw call audio, not transcripts, in front of more developers. Its pitch to teams running voice agents is a separate layer that spots cloned voices and grades how agents handle callers.

Perspective Coverage

3 publishers
Builder
Builder 40%
Operator
Operator 33%
Investor
Investor 27%

Reality

Evidence58
Adoption45
Hype gap+20
Incentives65
Confidence60
buildConfirmed6 publishers

Google splits transcription in two, and quietly absorbs your cleanup layer

Gemini 3.5 Transcribe ships as a sub-second streaming endpoint and a batch one, with filler-word removal and formatting inside the model. The catalog and the pricing page have not caught up.

Perspective Coverage

6 publishers
Builder
Builder 48%
Operator
Operator 36%
Investor
Investor 16%

Reality

Evidence55
Adoption35
Hype gap+25
Incentives70
Confidence60
buildOne report1 publisher

An evaluation-only preview licence gates NVIDIA's top-ranked diarization model

NVIDIA reports a 14.72% diarization error rate for the 100M-parameter Nemotron 3 Diarization, first on Voice Arena's initial leaderboard. Its Hugging Face preview page confines the weights to internal testing and evaluation.

Reality

Evidence55
Adoption
Not scored
Hype gap+30
Incentives65
Confidence60
buildOne report1 publisher

Six-word text matching caught four audiobooks that a filename check had cleared

The author of a Crimean Tatar recogniser scored it for the first time at 34.6% word error, then found four of his audiobooks sitting in the data twice under filenames a name check had cleared.

Publishers:dev.to

Reality

Evidence55
Adoption12
Hype gap−12
Incentives30
Confidence57
buildOne report1 publisher

A resident Whisper model plus embedding model together burned 2 euros of GPU electricity across 30 days

An RTX 3090 holding transcription and embedding models in VRAM averaged 25 W over the month at a cost of 2 euros, while the same post puts hardware amortisation at about 25 euros a month, twelve times the power bill.

Publishers:dev.to

Reality

Evidence35
Adoption10
Hype gap+25
Incentives50
Confidence40
buildOne report1 publisher

A 0.7 confidence gate lets 10 to 20 percent of wrong Whisper tokens through in noise

A developer's write-up of a medical transcription pipeline cites a 2025 study finding that under noise Whisper puts confidence above 0.7 on tokens that are wrong, and that the overconfidence grows as the signal-to-noise ratio falls.

Publishers:dev.to

Reality

Evidence35
Adoption10
Hype gap+28
Incentives65
Confidence40
buildOne report1 publisher

Ambiguity in Rule 1.3 pushes children's voice app toward on-device design

Apple's Kids Category rule and COPPA's definition of a child's voice both point a preschool voice product at local processing, and Whisper's error on children's speech falls by nearly a factor of three from tiny to large-v3.

Publishers:dev.to

Reality

Evidence47
Adoption38
Hype gap+9
Incentives71
Confidence54