Repository: ggerganov/whisper.cpp
File: whisper.h (C/C++)

Code before:
        bool no_timestamps;     // do not generate timestamps
        bool single_segment;    // force single segment output (useful for streaming)
        bool print_special;     // print special tokens (e.g. <SOT>, <EOT>, <BEG>, etc.)
        bool print_progress;    // print progress information
        bool print_realtime;    // print results from within whisper.cpp (avoid it, use callback instead)
        bool print_timestamps;  // print timestamps for each text segment when printing realtime

        // [EXPERIMENTAL] token-level timestamps
        bool  token_timestamps; // enable token-level timestamps
        float thold_pt;         // timestamp token probability threshold (~0.01)
        float thold_ptsum;      // timestamp token sum probability threshold (~0.01)
        int   max_len;          // max segment length in characters
        bool  split_on_word;    // split on word rather than on token (when used with max_len)
        int   max_tokens;       // max tokens per segment (0 = no limit)

        // [EXPERIMENTAL] speed-up techniques
        // note: these can significantly reduce the quality of the output
        bool speed_up;          // speed-up the audio by 2x using Phase Vocoder
        bool debug_mode;        // enable debug_mode provides extra info (eg. Dump log_mel)
        int  audio_ctx;         // overwrite the audio context size (0 = use default)

        // [EXPERIMENTAL] [TDRZ] tinydiarize
        bool tdrz_enable;       // enable tinydiarize speaker turn detection

        // A regular expression that matches tokens to suppress
        const char * suppress_tokens_re;

        // tokens to provide to the whisper decoder as initial prompt
        // these are prepended to any existing text context from a previous call
        // use whisper_tokenize() to convert text to tokens
        // maximum of whisper_n_text_ctx()/2 tokens are used (typically 224)
        const char * initial_prompt;
        const whisper_token * prompt_tokens;
        int prompt_n_tokens;

        // for auto-detection, set to nullptr, "" or "auto"
        const char * language;
        bool detect_language;

        // common decoding parameters:
        bool suppress_blank;    // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L89
        bool suppress_non_speech_tokens; // ref: https://github.com/openai/whisper/blob/7858aa9c08d98f75575035ecd6481f462d66ca27/whisper/tokenizer.py#L224-L253

        float temperature;      // initial decoding temperature, ref: https://ai.stackexchange.com/a/32478
        float max_initial_ts;   // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L97
        float length_penalty;   // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L267

        // fallback parameters
        // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L274-L278
        float temperature_inc;
        float entropy_thold;    // similar to OpenAI's "compression_ratio_threshold"

Review comment (suggestion):
```suggestion
        const char * suppress_regex;
```

Code after:
        bool no_timestamps;     // do not generate timestamps
        bool single_segment;    // force single segment output (useful for streaming)
        bool print_special;     // print special tokens (e.g. <SOT>, <EOT>, <BEG>, etc.)
        bool print_progress;    // print progress information
        bool print_realtime;    // print results from within whisper.cpp (avoid it, use callback instead)
        bool print_timestamps;  // print timestamps for each text segment when printing realtime

        // [EXPERIMENTAL] token-level timestamps
        bool  token_timestamps; // enable token-level timestamps
        float thold_pt;         // timestamp token probability threshold (~0.01)
        float thold_ptsum;      // timestamp token sum probability threshold (~0.01)
        int   max_len;          // max segment length in characters
        bool  split_on_word;    // split on word rather than on token (when used with max_len)
        int   max_tokens;       // max tokens per segment (0 = no limit)

        // [EXPERIMENTAL] speed-up techniques
        // note: these can significantly reduce the quality of the output
        bool speed_up;          // speed-up the audio by 2x using Phase Vocoder
        bool debug_mode;        // enable debug_mode provides extra info (eg. Dump log_mel)
        int  audio_ctx;         // overwrite the audio context size (0 = use default)

        // [EXPERIMENTAL] [TDRZ] tinydiarize
        bool tdrz_enable;       // enable tinydiarize speaker turn detection

        // A regular expression that matches tokens to suppress
        const char * suppress_regex;

        // tokens to provide to the whisper decoder as initial prompt
        // these are prepended to any existing text context from a previous call
        // use whisper_tokenize() to convert text to tokens
        // maximum of whisper_n_text_ctx()/2 tokens are used (typically 224)
        const char * initial_prompt;
        const whisper_token * prompt_tokens;
        int prompt_n_tokens;

        // for auto-detection, set to nullptr, "" or "auto"
        const char * language;
        bool detect_language;

        // common decoding parameters:
        bool suppress_blank;    // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L89
        bool suppress_non_speech_tokens; // ref: https://github.com/openai/whisper/blob/7858aa9c08d98f75575035ecd6481f462d66ca27/whisper/tokenizer.py#L224-L253

        float temperature;      // initial decoding temperature, ref: https://ai.stackexchange.com/a/32478
        float max_initial_ts;   // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L97
        float length_penalty;   // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L267

        // fallback parameters
        // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L274-L278
        float temperature_inc;
        float entropy_thold;    // similar to OpenAI's "compression_ratio_threshold"