The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

whisper 0.3.0

• Language auto-detection: transcribe() now defaults to language = NULL, which detects the spoken language from the audio before decoding. New exported function detect_language() for standalone language identification. Breaking: previous default was language = "en". Code relying on the default now auto-detects instead of assuming English. Pass language = "en" explicitly to restore old behavior.
• Segment-level and word-level timestamps via DTW alignment
• Beam search decoding with temperature sampling and fallback
• SDPA attention (FlashAttention on GPU)
• whisper_pipeline() for cached model reuse across multiple transcriptions
• Hardcoded special token table (eliminates added_tokens.json download)
• Fixed invalid multibyte string crash in BPE decoder
• Fixed DTW boundary guards and seek loop in transcribe_chunk()

whisper 0.1.0

• Initial CRAN submission
• Native R torch implementation of OpenAI Whisper
• Support for all model sizes: tiny, base, small, medium, large-v3
• Automatic model download from HuggingFace
• Model-specific special token handling for large-v3 compatibility
• KV caching for efficient autoregressive decoding
• Long audio chunking for files longer than 30 seconds
• Optional timestamp and segment extraction

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.