AI is happening. The future is updating.granite-speech-4.1-2b-nar
**Model Summary:** Granite-Speech-4.1-2B-NAR is a non-autoregressive (NAR) speech recognition model that formulates ASR as conditional transcript editing. Instead of decoding tokens one at a time, it edits a CTC hypothesis in a single forward pass using a bidirectional LLM, achieving competitive accuracy with faster inference than autoregressive alternatives. The model is based on the **NLE** (Non-autoregressive LLM-based Editing) architecture described in this paper. For applications where accuracy is the primary concern, consider **granite-speech-4.1-2b**, an autoregressive model from the Granite Speech 4.1 family which achieves higher transcription accuracy at the cost of increased inference latency. Granite-speech-4.1-2b produces punctuated and capitalized transcripts, supports AST and keyword-biased recognition, and includes Japanese. When speaker or word-timing information is needed, consider using **granite-speech-4.1-2b-plus**, which extends the above model with speaker-attributed ASR (speaker labels + word transcripts) and word-level timing information.
**Model Summary:** Granite-Speech-4.1-2B-NAR is a non-autoregressive (NAR) speech recognition model that formulates ASR as conditional transcript editing. Instead of decoding tokens one at a time, it edits a CTC hypothesis in a single forward pass using a bidirectional LLM, achieving competitive accuracy with faster inference than autoregressive alternatives. The model is based on the **NLE** (Non-autoregressive LLM-based Editing) architecture described in this paper. For applications where accuracy is the primary concern, consider **granite-speech-4.1-2b**, an autoregressive model from the Granite Speech 4.1 family which achieves higher transcription accuracy at the cost of increased inference latency. Granite-speech-4.1-2b produces punctuated and capitalized transcripts, supports AST and keyword-biased recognition, and includes Japanese. When speaker or word-timing information is needed, consider using **granite-speech-4.1-2b-plus**, which extends the above model with speaker-attributed ASR (speaker labels + word transcripts) and word-level timing information.