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Soniox STT v6 Adds Agent Text Input and Echo Filtering for Voice Agents

Soniox has released STT v6, a speech-to-text API update that introduces agent text input, allowing the model to read what the voice agent says while transcribing the caller, and model-level echo filtering to remove leaked agent audio. The update is available as stt-rt-v6 for streaming and stt-async-v6 for files, supporting 60+ languages, with pricing at $0.12/hour streaming and $0.10/hour async. No v6 benchmark numbers are published yet; v5 scored 1.34% semantic WER on Pipecat, and v5 models will be deprecated on December 15, 2026.

MarkTechPost1d agoScore 78

Soniox STT v6voice agent technologyspeech recognition

Research Editor selected

LipLingo: CNN Model for Lip Reading

LipLingo is a robust lip-reading system built on the LipNet architecture, incorporating a standardized preprocessing pipeline, rotational validation for speaker generalization, and flexible similarity evaluation for sentence-level assessment. Using 3D convolutional and bidirectional recurrent layers with CTC loss, it achieves 95.0% character accuracy and 87.2% sentence accuracy on the GRID dataset, outperforming the baseline LipNet. The work offers insights into improving lip-reading robustness for real-world deployment.

Why it matters: Presents a concrete, reproducible improvement in lip-reading accuracy with clear benchmarks, valuable for researchers and developers in speech recognition and assistive technology.

arxiv2d agoScore 82

lip readingdeep learningspeech recognition

Models Editor selected

NVIDIA Releases Nemotron 3.5 Transcribe Open Speech LLM

NVIDIA has released Nemotron 3.5 Transcribe, an open-weights speech LLM that handles 40 languages and recordings up to one hour from a single model. The hybrid Mamba-Transformer MoE has roughly 34B total and 4.3B active parameters, with built-in speaker attribution, word timestamps and prompt-selected output styles. NVIDIA reports 4.71% mean WER on nine English Open ASR sets, the best open-weights score, though commercial APIs still lead. Weights ship in BF16, FP8, NVFP4 and GGUF under a commercial-use license, with NVFP4 fitting an RTX 5090.

Why it matters: Developers get a concrete open, commercially licensed speech model that combines transcription, diarization, timestamps and translation, with deployment details and benchmark context.

MarkTechPostOct 29, 2026Score 88

NVIDIANemotronspeech recognition

Models Editor selected

Nvidia releases open Nemotron 3.5 Transcribe for transcription, translation, and speaker recognition

Nvidia has released Nemotron 3.5 Transcribe, an open speech recognition model that handles transcription, speaker recognition, and translation and accepts instructions as text prompts. Nvidia says it leads several benchmarks while using only one-sixth of the active parameters of its strongest open rival. The release also includes a dataset of more than 800,000 hours of speech and tools for fine-tuning.

Why it matters: It gives readers a concrete new open speech model release with combined capabilities, benchmark claims, and supporting data and fine-tuning tools.

The DecoderOct 28, 2026Score 86

Nvidiaspeech recognitionopen models

Models

Nvidia releases open transcription model for recorded audio

Nvidia has released a free speech-to-text model capable of transcribing up to 40 languages. The model works on recordings rather than live audio, positioning it for meeting and medical transcription use cases. It leaves real-time transcription to competitors such as ElevenLabs.

TechCrunch AIOct 28, 2026Score 74

Nvidiaspeech recognitionopen models

Models Editor selected

IBM Releases Granite Speech 5.0 2B, an Apache 2.0 Multilingual Speech Model

IBM released Granite Speech 5.0 2B, a 2B-parameter open speech-language model for transcription and translation in 6 languages under Apache 2.0. It combines a 16-block Conformer speech encoder with a window q-former and a fine-tuned granite-4.0-1b-base backbone, and adds language-ID prompting, keyword biasing up to 2,000 terms, and requested punctuation and capitalization. IBM reports 5.68% average English WER on the Open ASR Leaderboard, ranking second among open-weight models behind Qwen3-ASR-

Why it matters: Developers get a concrete, benchmarked open-weight ASR and translation release with deployment options and licensing details they can evaluate directly.

MarkTechPostOct 22, 2026Score 83

IBM Granitespeech recognitionopen-weight models

Tutorial

Independent CPU Benchmark Pits Cactus Whistle Against Whisper Base for Speech-to-Text

A MarkTechPost coding guide benchmarks Cactus Compute's 16.9 MB Whistle speech-to-text model against Whisper tiny and base on seeded LibriSpeech test-clean and test-other samples, using speaker-cluster bootstraps with Holm correction. The author reports a lead over greedy Whisper base on test-other and no significant gap against beam search, with a speed advantage that narrows on longer clips. The tutorial also documents a 30-second single-pass window where longer audio is silently truncated, pl

MarkTechPostOct 22, 2026Score 70

Cactus ComputeOpenAI Whisperspeech recognition

Products Editor selected

Mistral AI Releases Voxtral 3 Speech Models and LiveKit-Based Voice Agent SDK

Mistral AI launched Voxtral 3, a speech model family with three transcription models (Small, Mini and Mini Realtime) plus a text-to-speech model, all in public preview on the Mistral API. The release includes a voice agent SDK built on LiveKit that streams listening, LLM reasoning, tool calls and speech synthesis in one pipeline over SIP and WebRTC. Mistral reports 2.1% AA-WER for Small Transcribe 3 and 18.4% cpWER for diarization, while realtime accuracy lags Gemini 3.5 at low latency. Pricing

Why it matters: It gives AI builders concrete details on a new speech-to-text, TTS and voice-agent stack, including benchmarks, latency trade-offs and per-minute pricing that inform build-versus-buy decisions.

MarkTechPostOct 21, 2026Score 83

Mistral AIVoxtral 3speech recognition