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Open speech recognition stopped being a Whisper monoculture some time in the last twelve months. In March 2026 Cohere released Transcribe, a 2B Apache 2.0 model that took the top of the Hugging Face Open ASR Leaderboard at 5.42% average word error rate. Five weeks later IBM shipped Granite Speech 4.1 2B at 5.33%. Since […]
Automatic Music Transcription (AMT) converts an audio recording into symbolic notes, usually MIDI. Single-instrument transcription already works reasonably well. However, transcribing a full multi-instrument mix stays difficult. Kyutai and Mirelo team now release MuScriptor to close that gap. It is an open-weight model trained on real, multi-instrument recordings across many genres. This article explains how
Today, OpenAI released GPT-Live. It is a new generation of voice models. GPT-Live now powers the ChatGPT Voice experience. The stated goal is natural, real-time conversation with AI. Two versions ship first: GPT-Live-1 and GPT-Live-1 mini. Both roll out to ChatGPT users globally today. TL;DR GPT-Live is a full-duplex voice model family that listens and
NVIDIA has released Audex (Nemotron-Labs-Audex-30B-A3B), a unified audio-text large language model. It understands and generates both audio and speech. It also keeps the text intelligence of its backbone. The checkpoints, along with a smaller Audex-2B, are released under a noncommercial license. Most multimodal models pay a text tax. When labs add audio or vision output,
OpenAI has released two new Realtime models in its API. They are named gpt-realtime-2.1 and gpt-realtime-2.1-mini. Both target low-latency voice and multimodal experiences. The mini model is the notable part of this release. It is a mini reasoning model for realtime voice. It ships at the same cost as the earlier gpt-realtime-mini. OpenAI also reduced
Interfaze, a young YC’s startup, has open-sourced a new speech recognition model. It is called diffusion-gemma-asr-small. The model transcribes audio through a diffusion decoder, not an autoregressive one. It is described as the first multilingual audio diffusion ASR model. One adapter handles six languages. The research team trained only about 42M parameters on top of
Gradium today released two real-time speech translation models: stt-translate and s2s-translate. Both run across five languages and stream results live in the browser. Gradium claims a better accuracy-latency tradeoff than gpt-realtime-translate and gemini-3.5-live-translate. It also adds output voice control, including cloning, that gpt-realtime-translate lacks. TL;DR Gradium launched two real-time speech translation models: stt-translate (speech →
In this tutorial, we build a speech recognition and translation workflow using NVIDIA Canary-1B-v2. We begin by setting up the required audio, NeMo, NumPy, and SciPy dependencies, then load the Canary model on a GPU-enabled runtime for efficient inference. From there, we prepare audio into a clean 16 kHz mono format, perform English ASR, translate
Google just announced Gemini 3.5 Live Translate. It is their latest audio model for live speech-to-speech translation. Speech-to-speech means spoken audio goes in, and translated spoken audio comes out. The model detects over 70 languages automatically and generates translated speech. It preserves the speaker’s intonation, pacing, and pitch in the output. Turn-by-turn systems wait for
Last week Microsoft AI has announced MAI-Transcribe-1.5. It is the second iteration of the company’s in-house speech-to-text family. The model targets accuracy across 43 languages, accents, and noisy environments. The Microsoft team positions it for production transcription workloads. What is MAI-Transcribe-1.5 MAI-Transcribe-1.5 is an automatic speech recognition (ASR) model. It takes audio as input and
