AI Coding Live News

Microsoft AI announced on November 12 that MAI-Transcribe-2, its in-house speech-to-text model, is generally available in Microsoft Foundry for production use at $0.10 per hour of audio, a limited-time price through the end of 2026. The model entered public preview on September 3 and covers 60 languages in one model, with built-in speaker diarization, word-level timestamps and keyword biasing. Microsoft says it transcribes an hour of audio in about ten seconds of inference and averages 3.4% word error rate on the top 25 FLEURS languages.

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On November 13, DeepSeek said the capabilities behind the DeepSeek App are now available through its API. V4.1-Flash (model name deepseek-flash) supports server-side web search (including image search with citations), deep thinking search, file input for PDF, Office and image files, automatic reading of links in user messages, and input/output safety checks across the Messages, Responses and Chat Completions protocols. OCR, speech-to-text (ASR) and text-to-speech (TTS) also launch as standalone APIs. Tool calls are billed on top of token charges: Search and Fetch cost $0.75 per 1K requests, OCR $0.225 per 1K pages, ASR $0.058 per hour and TTS $0.225 per 10K characters (both at a limited-time 50% discount). DeepSeek also open-sourced an MIT-licensed chat front end that can import DeepSeek chat history. Public-facing apps must enable safety checks.

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At 00:30 Singapore time on November 13, Artificial Analysis (@ArtificialAnlys) posted that Salesforce's newly released SOV-Transcribe-1 is now the #1 open-weights speech-to-text model: 2.3% word error rate on the AA-WER Index, ranking 7th of 44 models including proprietary ones. That is 0.5 points better than the next open-weights models, Mistral Voxtral Small and NVIDIA Nemotron 3.5 Transcribe (both 2.8%). Built by Salesforce's Missionforce Sovereign AI team, the model has 26.6B total and 4.6B active parameters, pairs a Whisper large-v3 audio encoder with a Gemma 4 26B A4B MoE decoder, and ships on Hugging Face under Apache 2.0. It is non-streaming, so it suits recorded audio rather than live captions.

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On November 10 (02:10 on November 11 Singapore time) ElevenLabs released two speech-to-text models: Scribe v3 for recorded audio and Scribe v3 Live for realtime streams. By the vendor's numbers, Scribe v3 cuts word error rate (WER) by 27% versus Scribe v2 across 102 FLEURS languages, improving in every language, while Scribe v3 Live lowers semantic WER by 43% versus Scribe v2 Realtime and, for the first time, adds speaker diarization and context-aware turn detection to realtime transcription. Both models are live in ElevenAPI, where switching from v2 is a one-line model ID change; the API pricing page lists $0.20 per audio hour for v3 and $0.22 for v3 Live. Third-party evaluator Voice Arena tested v3 Live on 70+ hours of real phone calls and ranked it first in Romanian and Indian English.

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Voice model company Cartesia launched Managed Agents on Oct 29, an end-to-end voice agent platform for enterprise phone calls that tunes its own speech-to-text and text-to-speech models together with the agent harness, and bundles telephony, knowledge bases, tool calls and outbound batches. Cartesia says it ranks #1 on Artificial Analysis's Speech Agent Arena with a 1115 Elo and scores 87.4% accuracy and 90.7% experience on ServiceNow's EVA-Bench (vendor-reported, with GPT-5.5 as the reasoning model). Launch pricing is 50% off at $0.03 per minute.

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On Oct 20 Mistral released Voxtral 3: the Voxtral Small/Mini Transcribe 3 speech-to-text models, Voxtral Mini Transcribe Realtime 3, the Voxtral Mini TTS 3 (Voxtral Speech 3) text-to-speech model, and a LiveKit-based voice agent SDK that streams listening, reasoning with tool calls, and speaking as one pipeline, with each turn completing in under a second per Mistral. Transcription covers 50+ languages with diarization and context biasing; TTS covers 35+ languages and 50+ dialects, plus Pro Voice cloning from 30 minutes of audio. It is live on the Mistral API (EU, US and global endpoints) and can be self-deployed.

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