Introducing AnySpeechRecognizer and AnyDecisionModel: Open Models for Speech and Decisions on Apple Platforms

From the source

Language models can do a lot. They write, summarize, translate, and call tools. But they're only a small part of what machine learning can do.

Say a customer calls your support line. First, you want to know what they said (speech recognition). Then, you want to decide where to send them (decision). You could hand both to a language model, but there are models built for each that are better, faster, and less expensive.

In our AnyLanguageModel 1.0 recap , we looked at a year of local and hosted models in Swift. With AnyLanguageModel and swift-huggingface now on their 1.x releases, we're extending the same approach to speech and decisions: familiar Swift APIs with a choice of model.

Today we're announcing two packages:

AnySpeechRecognizer implements Apple's new speech-to-text API with a choice of recognition engine, including NVIDIA's Parakeet and Alibaba's Qwen3-ASR running locally on Core ML, and adds speaker diarization to track who speaks when.

AnyDecisionModel answers yes-or-no, multiple-choice, and rating-scale questions with typed results and probabilities.

huggingface.co