mirror of
https://github.com/ggerganov/whisper.cpp.git
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365 lines
16 KiB
C
365 lines
16 KiB
C
#ifndef WHISPER_H
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#define WHISPER_H
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#include <stddef.h>
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#include <stdint.h>
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#include <stdbool.h>
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#ifdef WHISPER_SHARED
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# ifdef _WIN32
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# ifdef WHISPER_BUILD
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# define WHISPER_API __declspec(dllexport)
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# else
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# define WHISPER_API __declspec(dllimport)
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# endif
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# else
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# define WHISPER_API __attribute__ ((visibility ("default")))
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# endif
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#else
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# define WHISPER_API
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#endif
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#define WHISPER_SAMPLE_RATE 16000
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#define WHISPER_N_FFT 400
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#define WHISPER_N_MEL 80
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#define WHISPER_HOP_LENGTH 160
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#define WHISPER_CHUNK_SIZE 30
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#ifdef __cplusplus
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extern "C" {
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#endif
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//
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// C interface
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//
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// The following interface is thread-safe as long as the sample whisper_context is not used by multiple threads
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// concurrently.
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//
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// Basic usage:
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//
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// #include "whisper.h"
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//
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// ...
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//
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// struct whisper_context * ctx = whisper_init_from_file("/path/to/ggml-base.en.bin");
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//
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// if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
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// fprintf(stderr, "failed to process audio\n");
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// return 7;
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// }
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//
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// const int n_segments = whisper_full_n_segments(ctx);
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// for (int i = 0; i < n_segments; ++i) {
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// const char * text = whisper_full_get_segment_text(ctx, i);
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// printf("%s", text);
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// }
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//
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// whisper_free(ctx);
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//
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// ...
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//
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// This is a demonstration of the most straightforward usage of the library.
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// "pcmf32" contains the RAW audio data in 32-bit floating point format.
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//
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// The interface also allows for more fine-grained control over the computation, but it requires a deeper
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// understanding of how the model works.
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//
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struct whisper_context;
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typedef int whisper_token;
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typedef struct whisper_token_data {
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whisper_token id; // token id
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whisper_token tid; // forced timestamp token id
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float p; // probability of the token
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float plog; // log probability of the token
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float pt; // probability of the timestamp token
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float ptsum; // sum of probabilities of all timestamp tokens
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// token-level timestamp data
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// do not use if you haven't computed token-level timestamps
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int64_t t0; // start time of the token
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int64_t t1; // end time of the token
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float vlen; // voice length of the token
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} whisper_token_data;
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typedef struct whisper_model_loader {
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void * context;
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size_t (*read)(void * ctx, void * output, size_t read_size);
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bool (*eof)(void * ctx);
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void (*close)(void * ctx);
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} whisper_model_loader;
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// Various functions for loading a ggml whisper model.
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// Allocate (almost) all memory needed for the model.
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// Return NULL on failure
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WHISPER_API struct whisper_context * whisper_init_from_file(const char * path_model);
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WHISPER_API struct whisper_context * whisper_init_from_buffer(void * buffer, size_t buffer_size);
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WHISPER_API struct whisper_context * whisper_init(struct whisper_model_loader * loader);
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// Frees all memory allocated by the model.
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WHISPER_API void whisper_free(struct whisper_context * ctx);
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// Convert RAW PCM audio to log mel spectrogram.
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// The resulting spectrogram is stored inside the provided whisper context.
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// Returns 0 on success
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WHISPER_API int whisper_pcm_to_mel(
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struct whisper_context * ctx,
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const float * samples,
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int n_samples,
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int n_threads);
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// This can be used to set a custom log mel spectrogram inside the provided whisper context.
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// Use this instead of whisper_pcm_to_mel() if you want to provide your own log mel spectrogram.
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// n_mel must be 80
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// Returns 0 on success
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WHISPER_API int whisper_set_mel(
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struct whisper_context * ctx,
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const float * data,
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int n_len,
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int n_mel);
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// Run the Whisper encoder on the log mel spectrogram stored inside the provided whisper context.
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// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first.
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// offset can be used to specify the offset of the first frame in the spectrogram.
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// Returns 0 on success
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WHISPER_API int whisper_encode(
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struct whisper_context * ctx,
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int offset,
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int n_threads);
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// Run the Whisper decoder to obtain the logits and probabilities for the next token.
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// Make sure to call whisper_encode() first.
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// tokens + n_tokens is the provided context for the decoder.
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// n_past is the number of tokens to use from previous decoder calls.
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// Returns 0 on success
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// TODO: add support for multiple decoders
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WHISPER_API int whisper_decode(
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struct whisper_context * ctx,
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const whisper_token * tokens,
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int n_tokens,
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int n_past,
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int n_threads);
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// Convert the provided text into tokens.
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// The tokens pointer must be large enough to hold the resulting tokens.
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// Returns the number of tokens on success, no more than n_max_tokens
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// Returns -1 on failure
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// TODO: not sure if correct
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WHISPER_API int whisper_tokenize(
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struct whisper_context * ctx,
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const char * text,
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whisper_token * tokens,
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int n_max_tokens);
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// Largest language id (i.e. number of available languages - 1)
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WHISPER_API int whisper_lang_max_id();
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// Return the id of the specified language, returns -1 if not found
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// Examples:
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// "de" -> 2
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// "german" -> 2
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WHISPER_API int whisper_lang_id(const char * lang);
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// Return the short string of the specified language id (e.g. 2 -> "de"), returns nullptr if not found
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WHISPER_API const char * whisper_lang_str(int id);
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// Use mel data at offset_ms to try and auto-detect the spoken language
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// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first
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// Returns the top language id or negative on failure
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// If not null, fills the lang_probs array with the probabilities of all languages
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// The array must be whispe_lang_max_id() + 1 in size
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// ref: https://github.com/openai/whisper/blob/main/whisper/decoding.py#L18-L69
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WHISPER_API int whisper_lang_auto_detect(
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struct whisper_context * ctx,
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int offset_ms,
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int n_threads,
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float * lang_probs);
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WHISPER_API int whisper_n_len (struct whisper_context * ctx); // mel length
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WHISPER_API int whisper_n_vocab (struct whisper_context * ctx);
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WHISPER_API int whisper_n_text_ctx (struct whisper_context * ctx);
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WHISPER_API int whisper_n_audio_ctx (struct whisper_context * ctx);
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WHISPER_API int whisper_is_multilingual(struct whisper_context * ctx);
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// Token logits obtained from the last call to whisper_decode()
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// The logits for the last token are stored in the last row
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// Rows: n_tokens
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// Cols: n_vocab
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WHISPER_API float * whisper_get_logits(struct whisper_context * ctx);
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// Token Id -> String. Uses the vocabulary in the provided context
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WHISPER_API const char * whisper_token_to_str(struct whisper_context * ctx, whisper_token token);
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// Special tokens
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WHISPER_API whisper_token whisper_token_eot (struct whisper_context * ctx);
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WHISPER_API whisper_token whisper_token_sot (struct whisper_context * ctx);
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WHISPER_API whisper_token whisper_token_prev(struct whisper_context * ctx);
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WHISPER_API whisper_token whisper_token_solm(struct whisper_context * ctx);
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WHISPER_API whisper_token whisper_token_not (struct whisper_context * ctx);
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WHISPER_API whisper_token whisper_token_beg (struct whisper_context * ctx);
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WHISPER_API whisper_token whisper_token_lang(struct whisper_context * ctx, int lang_id);
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// Task tokens
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WHISPER_API whisper_token whisper_token_translate (void);
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WHISPER_API whisper_token whisper_token_transcribe(void);
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// Performance information
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WHISPER_API void whisper_print_timings(struct whisper_context * ctx);
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WHISPER_API void whisper_reset_timings(struct whisper_context * ctx);
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// Print system information
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WHISPER_API const char * whisper_print_system_info(void);
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////////////////////////////////////////////////////////////////////////////
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// Available sampling strategies
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enum whisper_sampling_strategy {
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WHISPER_SAMPLING_GREEDY, // similar to OpenAI's GreefyDecoder
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WHISPER_SAMPLING_BEAM_SEARCH, // similar to OpenAI's BeamSearchDecoder
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};
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// Text segment callback
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// Called on every newly generated text segment
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// Use the whisper_full_...() functions to obtain the text segments
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typedef void (*whisper_new_segment_callback)(struct whisper_context * ctx, int n_new, void * user_data);
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// Encoder begin callback
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// If not NULL, called before the encoder starts
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// If it returns false, the computation is aborted
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typedef bool (*whisper_encoder_begin_callback)(struct whisper_context * ctx, void * user_data);
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// Parameters for the whisper_full() function
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// If you chnage the order or add new parameters, make sure to update the default values in whisper.cpp:
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// whisper_full_default_params()
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struct whisper_full_params {
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enum whisper_sampling_strategy strategy;
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int n_threads;
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int n_max_text_ctx; // max tokens to use from past text as prompt for the decoder
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int offset_ms; // start offset in ms
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int duration_ms; // audio duration to process in ms
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bool translate;
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bool no_context; // do not use past transcription (if any) as initial prompt for the decoder
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bool single_segment; // force single segment output (useful for streaming)
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bool print_special; // print special tokens (e.g. <SOT>, <EOT>, <BEG>, etc.)
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bool print_progress; // print progress information
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bool print_realtime; // print results from within whisper.cpp (avoid it, use callback instead)
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bool print_timestamps; // print timestamps for each text segment when printing realtime
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// [EXPERIMENTAL] token-level timestamps
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bool token_timestamps; // enable token-level timestamps
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float thold_pt; // timestamp token probability threshold (~0.01)
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float thold_ptsum; // timestamp token sum probability threshold (~0.01)
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int max_len; // max segment length in characters
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int max_tokens; // max tokens per segment (0 = no limit)
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// [EXPERIMENTAL] speed-up techniques
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// note: these can significantly reduce the quality of the output
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bool speed_up; // speed-up the audio by 2x using Phase Vocoder
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int audio_ctx; // overwrite the audio context size (0 = use default)
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// tokens to provide to the whisper decoder as initial prompt
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// these are prepended to any existing text context from a previous call
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const whisper_token * prompt_tokens;
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int prompt_n_tokens;
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// for auto-detection, set to nullptr, "" or "auto"
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const char * language;
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// common decoding parameters:
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bool suppress_blank; // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L89
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float temperature; // initial decoding temperature, ref: https://ai.stackexchange.com/a/32478
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float max_initial_ts; // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L97
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float length_penalty; // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L267
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// fallback parameters
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// ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L274-L278
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float temperature_inc;
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float entropy_thold; // similar to OpenAI's "compression_ratio_threshold"
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float logprob_thold;
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float no_speech_thold; // TODO: not implemented
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struct {
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int best_of; // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L264
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} greedy;
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struct {
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int beam_size; // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L265
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float patience; // TODO: not implemented, ref: https://arxiv.org/pdf/2204.05424.pdf
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} beam_search;
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// called for every newly generated text segment
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whisper_new_segment_callback new_segment_callback;
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void * new_segment_callback_user_data;
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// called each time before the encoder starts
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whisper_encoder_begin_callback encoder_begin_callback;
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void * encoder_begin_callback_user_data;
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};
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WHISPER_API struct whisper_full_params whisper_full_default_params(enum whisper_sampling_strategy strategy);
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// Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
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// Uses the specified decoding strategy to obtain the text.
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WHISPER_API int whisper_full(
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struct whisper_context * ctx,
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struct whisper_full_params params,
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const float * samples,
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int n_samples);
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// Split the input audio in chunks and process each chunk separately using whisper_full()
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// It seems this approach can offer some speedup in some cases.
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// However, the transcription accuracy can be worse at the beginning and end of each chunk.
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WHISPER_API int whisper_full_parallel(
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struct whisper_context * ctx,
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struct whisper_full_params params,
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const float * samples,
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int n_samples,
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int n_processors);
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// Number of generated text segments.
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// A segment can be a few words, a sentence, or even a paragraph.
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WHISPER_API int whisper_full_n_segments(struct whisper_context * ctx);
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// Get the start and end time of the specified segment.
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WHISPER_API int64_t whisper_full_get_segment_t0(struct whisper_context * ctx, int i_segment);
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WHISPER_API int64_t whisper_full_get_segment_t1(struct whisper_context * ctx, int i_segment);
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// Get the text of the specified segment.
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WHISPER_API const char * whisper_full_get_segment_text(struct whisper_context * ctx, int i_segment);
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// Get number of tokens in the specified segment.
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WHISPER_API int whisper_full_n_tokens(struct whisper_context * ctx, int i_segment);
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// Get the token text of the specified token in the specified segment.
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WHISPER_API const char * whisper_full_get_token_text(struct whisper_context * ctx, int i_segment, int i_token);
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WHISPER_API whisper_token whisper_full_get_token_id (struct whisper_context * ctx, int i_segment, int i_token);
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// Get token data for the specified token in the specified segment.
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// This contains probabilities, timestamps, etc.
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WHISPER_API whisper_token_data whisper_full_get_token_data(struct whisper_context * ctx, int i_segment, int i_token);
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// Get the probability of the specified token in the specified segment.
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WHISPER_API float whisper_full_get_token_p(struct whisper_context * ctx, int i_segment, int i_token);
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////////////////////////////////////////////////////////////////////////////
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// Temporary helpers needed for exposing ggml interface
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WHISPER_API int whisper_bench_memcpy(int n_threads);
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WHISPER_API int whisper_bench_ggml_mul_mat(int n_threads);
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#ifdef __cplusplus
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}
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#endif
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#endif
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