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