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feat: publish v1.0.1

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Signed-off-by: 小草林(田梓萱) <xcl@xuegao-tzx.top>
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田梓萱
2024-06-12 09:52:36 +08:00
parent 2e87763b84
commit af91fc48cb
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*.o
*.a
.cache/
.vs/
.vscode/
.DS_Store
build/
build-em/
build-debug/
build-release/
build-static/
build-sanitize-addr/
build-sanitize-thread/
/main
/stream
/command
/talk
/bench
arm_neon.h
sync.sh
libwhisper.a
libwhisper.so
compile_commands.json

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#ifndef WHISPER_H
#define WHISPER_H
#include <stddef.h>
#include <stdint.h>
#include <stdbool.h>
#ifdef WHISPER_SHARED
# ifdef _WIN32
# ifdef WHISPER_BUILD
# define WHISPER_API __declspec(dllexport)
# else
# define WHISPER_API __declspec(dllimport)
# endif
# else
# define WHISPER_API __attribute__ ((visibility ("default")))
# endif
#else
# define WHISPER_API
#endif
#define WHISPER_SAMPLE_RATE 16000
#define WHISPER_N_FFT 400
#define WHISPER_N_MEL 80
#define WHISPER_HOP_LENGTH 160
#define WHISPER_CHUNK_SIZE 30
#ifdef __cplusplus
extern "C" {
#endif
//
// C interface
//
// The following interface is thread-safe as long as the sample whisper_context is not used by multiple threads
// concurrently.
//
// Basic usage:
//
// #include "whisper.h"
//
// ...
//
// struct whisper_context * ctx = whisper_init_from_file("/path/to/ggml-base.en.bin");
//
// if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
// fprintf(stderr, "failed to process audio\n");
// return 7;
// }
//
// const int n_segments = whisper_full_n_segments(ctx);
// for (int i = 0; i < n_segments; ++i) {
// const char * text = whisper_full_get_segment_text(ctx, i);
// printf("%s", text);
// }
//
// whisper_free(ctx);
//
// ...
//
// This is a demonstration of the most straightforward usage of the library.
// "pcmf32" contains the RAW audio data in 32-bit floating point format.
//
// The interface also allows for more fine-grained control over the computation, but it requires a deeper
// understanding of how the model works.
//
struct whisper_context;
struct whisper_state;
struct whisper_full_params;
typedef int whisper_token;
typedef struct whisper_token_data {
whisper_token id; // token id
whisper_token tid; // forced timestamp token id
float p; // probability of the token
float plog; // log probability of the token
float pt; // probability of the timestamp token
float ptsum; // sum of probabilities of all timestamp tokens
// token-level timestamp data
// do not use if you haven't computed token-level timestamps
int64_t t0; // start time of the token
int64_t t1; // end time of the token
float vlen; // voice length of the token
} whisper_token_data;
typedef struct whisper_model_loader {
void * context;
size_t (*read)(void * ctx, void * output, size_t read_size);
bool (*eof)(void * ctx);
void (*close)(void * ctx);
} whisper_model_loader;
// Various functions for loading a ggml whisper model.
// Allocate (almost) all memory needed for the model.
// Return NULL on failure
WHISPER_API struct whisper_context * whisper_init_from_file(const char * path_model);
WHISPER_API struct whisper_context * whisper_init_from_buffer(void * buffer, size_t buffer_size);
WHISPER_API struct whisper_context * whisper_init(struct whisper_model_loader * loader);
// These are the same as the above, but the internal state of the context is not allocated automatically
// It is the responsibility of the caller to allocate the state using whisper_init_state() (#523)
WHISPER_API struct whisper_context * whisper_init_from_file_no_state(const char * path_model);
WHISPER_API struct whisper_context * whisper_init_from_buffer_no_state(void * buffer, size_t buffer_size);
WHISPER_API struct whisper_context * whisper_init_no_state(struct whisper_model_loader * loader);
WHISPER_API struct whisper_state * whisper_init_state(struct whisper_context * ctx);
// Given a context, enable use of OpenVINO for encode inference.
// model_path: Optional path to OpenVINO encoder IR model. If set to nullptr,
// the path will be generated from the ggml model path that was passed
// in to whisper_init_from_file. For example, if 'path_model' was
// "/path/to/ggml-base.en.bin", then OpenVINO IR model path will be
// assumed to be "/path/to/ggml-base.en-encoder-openvino.xml".
// device: OpenVINO device to run inference on ("CPU", "GPU", etc.)
// cache_dir: Optional cache directory that can speed up init time, especially for
// GPU, by caching compiled 'blobs' there.
// Set to nullptr if not used.
// Returns 0 on success. If OpenVINO is not enabled in build, this simply returns 1.
WHISPER_API int whisper_ctx_init_openvino_encoder(
struct whisper_context * ctx,
const char * model_path,
const char * device,
const char * cache_dir);
// Frees all allocated memory
WHISPER_API void whisper_free (struct whisper_context * ctx);
WHISPER_API void whisper_free_state(struct whisper_state * state);
WHISPER_API void whisper_free_params(struct whisper_full_params * params);
// Convert RAW PCM audio to log mel spectrogram.
// The resulting spectrogram is stored inside the default state of the provided whisper context.
// Returns 0 on success
WHISPER_API int whisper_pcm_to_mel(
struct whisper_context * ctx,
const float * samples,
int n_samples,
int n_threads);
WHISPER_API int whisper_pcm_to_mel_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
const float * samples,
int n_samples,
int n_threads);
// Convert RAW PCM audio to log mel spectrogram but applies a Phase Vocoder to speed up the audio x2.
// The resulting spectrogram is stored inside the default state of the provided whisper context.
// Returns 0 on success
WHISPER_API int whisper_pcm_to_mel_phase_vocoder(
struct whisper_context * ctx,
const float * samples,
int n_samples,
int n_threads);
WHISPER_API int whisper_pcm_to_mel_phase_vocoder_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
const float * samples,
int n_samples,
int n_threads);
// This can be used to set a custom log mel spectrogram inside the default state of the provided whisper context.
// Use this instead of whisper_pcm_to_mel() if you want to provide your own log mel spectrogram.
// n_mel must be 80
// Returns 0 on success
WHISPER_API int whisper_set_mel(
struct whisper_context * ctx,
const float * data,
int n_len,
int n_mel);
WHISPER_API int whisper_set_mel_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
const float * data,
int n_len,
int n_mel);
// Run the Whisper encoder on the log mel spectrogram stored inside the default state in the provided whisper context.
// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first.
// offset can be used to specify the offset of the first frame in the spectrogram.
// Returns 0 on success
WHISPER_API int whisper_encode(
struct whisper_context * ctx,
int offset,
int n_threads);
WHISPER_API int whisper_encode_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
int offset,
int n_threads);
// Run the Whisper decoder to obtain the logits and probabilities for the next token.
// Make sure to call whisper_encode() first.
// tokens + n_tokens is the provided context for the decoder.
// n_past is the number of tokens to use from previous decoder calls.
// Returns 0 on success
// TODO: add support for multiple decoders
WHISPER_API int whisper_decode(
struct whisper_context * ctx,
const whisper_token * tokens,
int n_tokens,
int n_past,
int n_threads);
WHISPER_API int whisper_decode_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
const whisper_token * tokens,
int n_tokens,
int n_past,
int n_threads);
// Convert the provided text into tokens.
// The tokens pointer must be large enough to hold the resulting tokens.
// Returns the number of tokens on success, no more than n_max_tokens
// Returns -1 on failure
// TODO: not sure if correct
WHISPER_API int whisper_tokenize(
struct whisper_context * ctx,
const char * text,
whisper_token * tokens,
int n_max_tokens);
// Largest language id (i.e. number of available languages - 1)
WHISPER_API int whisper_lang_max_id();
// Return the id of the specified language, returns -1 if not found
// Examples:
// "de" -> 2
// "german" -> 2
WHISPER_API int whisper_lang_id(const char * lang);
// Return the short string of the specified language id (e.g. 2 -> "de"), returns nullptr if not found
WHISPER_API const char * whisper_lang_str(int id);
// Use mel data at offset_ms to try and auto-detect the spoken language
// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first
// Returns the top language id or negative on failure
// If not null, fills the lang_probs array with the probabilities of all languages
// The array must be whisper_lang_max_id() + 1 in size
// ref: https://github.com/openai/whisper/blob/main/whisper/decoding.py#L18-L69
WHISPER_API int whisper_lang_auto_detect(
struct whisper_context * ctx,
int offset_ms,
int n_threads,
float * lang_probs);
WHISPER_API int whisper_lang_auto_detect_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
int offset_ms,
int n_threads,
float * lang_probs);
WHISPER_API int whisper_n_len (struct whisper_context * ctx); // mel length
WHISPER_API int whisper_n_len_from_state(struct whisper_state * state); // mel length
WHISPER_API int whisper_n_vocab (struct whisper_context * ctx);
WHISPER_API int whisper_n_text_ctx (struct whisper_context * ctx);
WHISPER_API int whisper_n_audio_ctx (struct whisper_context * ctx);
WHISPER_API int whisper_is_multilingual (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_vocab (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_audio_ctx (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_audio_state(struct whisper_context * ctx);
WHISPER_API int whisper_model_n_audio_head (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_audio_layer(struct whisper_context * ctx);
WHISPER_API int whisper_model_n_text_ctx (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_text_state (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_text_head (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_text_layer (struct whisper_context * ctx);
WHISPER_API int whisper_model_n_mels (struct whisper_context * ctx);
WHISPER_API int whisper_model_ftype (struct whisper_context * ctx);
WHISPER_API int whisper_model_type (struct whisper_context * ctx);
// Token logits obtained from the last call to whisper_decode()
// The logits for the last token are stored in the last row
// Rows: n_tokens
// Cols: n_vocab
WHISPER_API float * whisper_get_logits (struct whisper_context * ctx);
WHISPER_API float * whisper_get_logits_from_state(struct whisper_state * state);
// Token Id -> String. Uses the vocabulary in the provided context
WHISPER_API const char * whisper_token_to_str(struct whisper_context * ctx, whisper_token token);
WHISPER_API const char * whisper_model_type_readable(struct whisper_context * ctx);
// Special tokens
WHISPER_API whisper_token whisper_token_eot (struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_sot (struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_solm(struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_prev(struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_nosp(struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_not (struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_beg (struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_lang(struct whisper_context * ctx, int lang_id);
// Task tokens
WHISPER_API whisper_token whisper_token_translate (struct whisper_context * ctx);
WHISPER_API whisper_token whisper_token_transcribe(struct whisper_context * ctx);
// Performance information from the default state.
WHISPER_API void whisper_print_timings(struct whisper_context * ctx);
WHISPER_API void whisper_reset_timings(struct whisper_context * ctx);
// Print system information
WHISPER_API const char * whisper_print_system_info(void);
////////////////////////////////////////////////////////////////////////////
// Available sampling strategies
enum whisper_sampling_strategy {
WHISPER_SAMPLING_GREEDY, // similar to OpenAI's GreedyDecoder
WHISPER_SAMPLING_BEAM_SEARCH, // similar to OpenAI's BeamSearchDecoder
};
// Text segment callback
// Called on every newly generated text segment
// Use the whisper_full_...() functions to obtain the text segments
typedef void (*whisper_new_segment_callback)(struct whisper_context * ctx, struct whisper_state * state, int n_new, void * user_data);
// Progress callback
typedef void (*whisper_progress_callback)(struct whisper_context * ctx, struct whisper_state * state, int progress, void * user_data);
// Encoder begin callback
// If not NULL, called before the encoder starts
// If it returns false, the computation is aborted
typedef bool (*whisper_encoder_begin_callback)(struct whisper_context * ctx, struct whisper_state * state, void * user_data);
// Logits filter callback
// Can be used to modify the logits before sampling
// If not NULL, called after applying temperature to logits
typedef void (*whisper_logits_filter_callback)(
struct whisper_context * ctx,
struct whisper_state * state,
const whisper_token_data * tokens,
int n_tokens,
float * logits,
void * user_data);
// Parameters for the whisper_full() function
// If you chnage the order or add new parameters, make sure to update the default values in whisper.cpp:
// whisper_full_default_params()
struct whisper_full_params {
enum whisper_sampling_strategy strategy;
int n_threads;
int n_max_text_ctx; // max tokens to use from past text as prompt for the decoder
int offset_ms; // start offset in ms
int duration_ms; // audio duration to process in ms
bool translate;
bool no_context; // do not use past transcription (if any) as initial prompt for the decoder
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
int audio_ctx; // overwrite the audio context size (0 = use default)
// [EXPERIMENTAL] [TDRZ] tinydiarize
bool tdrz_enable; // enable tinydiarize speaker turn detection
// tokens to provide to the whisper decoder as initial prompt
// these are prepended to any existing text context from a previous call
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"
float logprob_thold;
float no_speech_thold; // TODO: not implemented
struct {
int best_of; // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L264
} greedy;
struct {
int beam_size; // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L265
float patience; // TODO: not implemented, ref: https://arxiv.org/pdf/2204.05424.pdf
} beam_search;
// called for every newly generated text segment
whisper_new_segment_callback new_segment_callback;
void * new_segment_callback_user_data;
// called on each progress update
whisper_progress_callback progress_callback;
void * progress_callback_user_data;
// called each time before the encoder starts
whisper_encoder_begin_callback encoder_begin_callback;
void * encoder_begin_callback_user_data;
// called by each decoder to filter obtained logits
whisper_logits_filter_callback logits_filter_callback;
void * logits_filter_callback_user_data;
};
// NOTE: this function allocates memory, and it is the responsibility of the caller to free the pointer - see whisper_free_params()
WHISPER_API struct whisper_full_params * whisper_full_default_params_by_ref(enum whisper_sampling_strategy strategy);
WHISPER_API struct whisper_full_params whisper_full_default_params(enum whisper_sampling_strategy strategy);
// Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
// Not thread safe for same context
// Uses the specified decoding strategy to obtain the text.
WHISPER_API int whisper_full(
struct whisper_context * ctx,
struct whisper_full_params params,
const float * samples,
int n_samples);
WHISPER_API int whisper_full_with_state(
struct whisper_context * ctx,
struct whisper_state * state,
struct whisper_full_params params,
const float * samples,
int n_samples);
// Split the input audio in chunks and process each chunk separately using whisper_full_with_state()
// Result is stored in the default state of the context
// Not thread safe if executed in parallel on the same context.
// It seems this approach can offer some speedup in some cases.
// However, the transcription accuracy can be worse at the beginning and end of each chunk.
WHISPER_API int whisper_full_parallel(
struct whisper_context * ctx,
struct whisper_full_params params,
const float * samples,
int n_samples,
int n_processors);
// Number of generated text segments
// A segment can be a few words, a sentence, or even a paragraph.
WHISPER_API int whisper_full_n_segments (struct whisper_context * ctx);
WHISPER_API int whisper_full_n_segments_from_state(struct whisper_state * state);
// Language id associated with the context's default state
WHISPER_API int whisper_full_lang_id(struct whisper_context * ctx);
// Language id associated with the provided state
WHISPER_API int whisper_full_lang_id_from_state(struct whisper_state * state);
// Get the start and end time of the specified segment
WHISPER_API int64_t whisper_full_get_segment_t0 (struct whisper_context * ctx, int i_segment);
WHISPER_API int64_t whisper_full_get_segment_t0_from_state(struct whisper_state * state, int i_segment);
WHISPER_API int64_t whisper_full_get_segment_t1 (struct whisper_context * ctx, int i_segment);
WHISPER_API int64_t whisper_full_get_segment_t1_from_state(struct whisper_state * state, int i_segment);
// Get whether the next segment is predicted as a speaker turn
WHISPER_API bool whisper_full_get_segment_speaker_turn_next(struct whisper_context * ctx, int i_segment);
// Get the text of the specified segment
WHISPER_API const char * whisper_full_get_segment_text (struct whisper_context * ctx, int i_segment);
WHISPER_API const char * whisper_full_get_segment_text_from_state(struct whisper_state * state, int i_segment);
// Get number of tokens in the specified segment
WHISPER_API int whisper_full_n_tokens (struct whisper_context * ctx, int i_segment);
WHISPER_API int whisper_full_n_tokens_from_state(struct whisper_state * state, int i_segment);
// Get the token text of the specified token in the specified segment
WHISPER_API const char * whisper_full_get_token_text (struct whisper_context * ctx, int i_segment, int i_token);
WHISPER_API const char * whisper_full_get_token_text_from_state(struct whisper_context * ctx, struct whisper_state * state, int i_segment, int i_token);
WHISPER_API whisper_token whisper_full_get_token_id (struct whisper_context * ctx, int i_segment, int i_token);
WHISPER_API whisper_token whisper_full_get_token_id_from_state(struct whisper_state * state, int i_segment, int i_token);
// Get token data for the specified token in the specified segment
// This contains probabilities, timestamps, etc.
WHISPER_API whisper_token_data whisper_full_get_token_data (struct whisper_context * ctx, int i_segment, int i_token);
WHISPER_API whisper_token_data whisper_full_get_token_data_from_state(struct whisper_state * state, int i_segment, int i_token);
// Get the probability of the specified token in the specified segment
WHISPER_API float whisper_full_get_token_p (struct whisper_context * ctx, int i_segment, int i_token);
WHISPER_API float whisper_full_get_token_p_from_state(struct whisper_state * state, int i_segment, int i_token);
////////////////////////////////////////////////////////////////////////////
// Temporary helpers needed for exposing ggml interface
WHISPER_API int whisper_bench_memcpy (int n_threads);
WHISPER_API const char * whisper_bench_memcpy_str (int n_threads);
WHISPER_API int whisper_bench_ggml_mul_mat (int n_threads);
WHISPER_API const char * whisper_bench_ggml_mul_mat_str(int n_threads);
// Control logging output; default behavior is to print to stderr
typedef void (*whisper_log_callback)(const char * line);
WHISPER_API void whisper_set_log_callback(whisper_log_callback callback);
#ifdef __cplusplus
}
#endif
#endif

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#include "whisper_flutter_new.h"
#include "whisper.cpp/whisper.h"
#define DR_WAV_IMPLEMENTATION
#include "whisper.cpp/examples/dr_wav.h"
#include <cstdio>
#include <string>
#include <thread>
#include <vector>
#include <cmath>
#include <iostream>
#include <stdio.h>
#include "json/json.hpp"
using json = nlohmann::json;
char *jsonToChar(json jsonData) noexcept
{
std::string result = jsonData.dump();
char *ch = new char[result.size() + 1];
strcpy(ch, result.c_str());
return ch;
}
struct whisper_params
{
int32_t seed = -1; // RNG seed, not used currently
int32_t n_threads = std::min(4, (int32_t)std::thread::hardware_concurrency());
int32_t n_processors = 1;
int32_t offset_t_ms = 0;
int32_t offset_n = 0;
int32_t duration_ms = 0;
int32_t max_context = -1;
int32_t max_len = 0;
int32_t best_of = 5;
int32_t beam_size = -1;
float word_thold = 0.01f;
float entropy_thold = 2.40f;
float logprob_thold = -1.00f;
bool verbose = false;
bool print_special_tokens = false;
bool speed_up = false;
bool translate = false;
bool diarize = false;
bool no_fallback = false;
bool output_txt = false;
bool output_vtt = false;
bool output_srt = false;
bool output_wts = false;
bool output_csv = false;
bool print_special = false;
bool print_colors = false;
bool print_progress = false;
bool no_timestamps = false;
bool split_on_word = false;
std::string language = "auto";
std::string prompt;
std::string model = "models/ggml-tiny.bin";
std::string audio = "samples/jfk.wav";
std::vector<std::string> fname_inp = {};
std::vector<std::string> fname_outp = {};
};
struct whisper_print_user_data
{
const whisper_params *params;
const std::vector<std::vector<float>> *pcmf32s;
};
json transcribe(json jsonBody) noexcept
{
whisper_params params;
params.n_threads = jsonBody["threads"];
params.verbose = jsonBody["is_verbose"];
params.translate = jsonBody["is_translate"];
params.language = jsonBody["language"];
params.print_special_tokens = jsonBody["is_special_tokens"];
params.no_timestamps = jsonBody["is_no_timestamps"];
params.model = jsonBody["model"];
params.audio = jsonBody["audio"];
params.split_on_word = jsonBody["split_on_word"];
json jsonResult;
jsonResult["@type"] = "transcribe";
if (params.language != "" && params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1)
{
jsonResult["@type"] = "error";
jsonResult["message"] = "error: unknown language = " + params.language;
return jsonResult;
}
if (params.seed < 0)
{
params.seed = time(NULL);
}
// whisper init
struct whisper_context *ctx = whisper_init_from_file(params.model.c_str());
std::string text_result = "";
const auto fname_inp = params.audio;
// WAV input
std::vector<float> pcmf32;
{
drwav wav;
if (!drwav_init_file(&wav, fname_inp.c_str(), NULL))
{
jsonResult["@type"] = "error";
jsonResult["message"] = " failed to open WAV file ";
return jsonResult;
}
if (wav.channels != 1 && wav.channels != 2)
{
jsonResult["@type"] = "error";
jsonResult["message"] = "must be mono or stereo";
return jsonResult;
}
if (wav.sampleRate != WHISPER_SAMPLE_RATE)
{
jsonResult["@type"] = "error";
jsonResult["message"] = "WAV file must be 16 kHz";
return jsonResult;
}
if (wav.bitsPerSample != 16)
{
jsonResult["@type"] = "error";
jsonResult["message"] = "WAV file must be 16 bit";
return jsonResult;
}
int n = wav.totalPCMFrameCount;
std::vector<int16_t> pcm16;
pcm16.resize(n * wav.channels);
drwav_read_pcm_frames_s16(&wav, n, pcm16.data());
drwav_uninit(&wav);
// convert to mono, float
pcmf32.resize(n);
if (wav.channels == 1)
{
for (int i = 0; i < n; i++)
{
pcmf32[i] = float(pcm16[i]) / 32768.0f;
}
}
else
{
for (int i = 0; i < n; i++)
{
pcmf32[i] = float(pcm16[2 * i] + pcm16[2 * i + 1]) / 65536.0f;
}
}
}
{
if (params.language == "" && params.language == "auto")
{
params.language = "auto";
params.translate = false;
}
}
// run the inference
{
whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
wparams.print_realtime = false;
wparams.print_progress = false;
wparams.print_timestamps = !params.no_timestamps;
// wparams.print_special_tokens = params.print_special_tokens;
wparams.translate = params.translate;
wparams.language = params.language.c_str();
wparams.n_threads = params.n_threads;
wparams.split_on_word = params.split_on_word;
if (params.split_on_word) {
wparams.max_len = 1;
wparams.token_timestamps = true;
}
if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0)
{
jsonResult["@type"] = "error";
jsonResult["message"] = "failed to process audio";
return jsonResult;
}
// print result;
if (!wparams.print_realtime)
{
const int n_segments = whisper_full_n_segments(ctx);
std::vector<json> segmentsJson = {};
for (int i = 0; i < n_segments; ++i)
{
const char *text = whisper_full_get_segment_text(ctx, i);
std::string str(text);
text_result += str;
if (params.no_timestamps)
{
// printf("%s", text);
// fflush(stdout);
} else {
json jsonSegment;
const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
// printf("[%s --> %s] %s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), text);
jsonSegment["from_ts"] = t0;
jsonSegment["to_ts"] = t1;
jsonSegment["text"] = text;
segmentsJson.push_back(jsonSegment);
}
}
if (!params.no_timestamps) {
jsonResult["segments"] = segmentsJson;
}
}
}
jsonResult["text"] = text_result;
whisper_free(ctx);
return jsonResult;
}
extern "C"
{
FUNCTION_ATTRIBUTE
char *request(char *body)
{
try
{
json jsonBody = json::parse(body);
json jsonResult;
if (jsonBody["@type"] == "getTextFromWavFile")
{
try
{
return jsonToChar(transcribe(jsonBody));
}
catch (const std::exception &e)
{
jsonResult["@type"] = "error";
jsonResult["message"] = e.what();
return jsonToChar(jsonResult);
}
}
if (jsonBody["@type"] == "getVersion")
{
jsonResult["@type"] = "version";
jsonResult["message"] = "lib version: v1.0.1";
return jsonToChar(jsonResult);
}
jsonResult["@type"] = "error";
jsonResult["message"] = "method not found";
return jsonToChar(jsonResult);
}
catch (const std::exception &e)
{
json jsonResult;
jsonResult["@type"] = "error";
jsonResult["message"] = e.what();
return jsonToChar(jsonResult);
}
}
}

18
ios/Classes/whisper_flutter_new.h Normal file
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@@ -0,0 +1,18 @@
#if defined(__GNUC__)
// Attributes to prevent 'unused' function from being removed and to make it visible
#define FUNCTION_ATTRIBUTE __attribute__((visibility("default"))) __attribute__((used))
#elif defined(_MSC_VER)
// Marking a function for export
#define FUNCTION_ATTRIBUTE __declspec(dllexport)
#endif
#ifdef __cplusplus
extern "C"
{
#endif
char *request(char *body);
#ifdef __cplusplus
}
#endif

36
ios/whisper_flutter_new.podspec Normal file
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@@ -0,0 +1,36 @@
#
# To learn more about a Podspec see http://guides.cocoapods.org/syntax/podspec.html.
# Run `pod lib lint whisper_flutter.podspec` to validate before publishing.
#
Pod::Spec.new do |s|
s.name = 'whisper_flutter_new'
s.version = '0.0.1'
s.summary = 'A Flutter FFI plugin for Whisper.cpp.'
s.description = <<-DESC
A Flutter FFI plugin for Whisper.cpp.
DESC
s.homepage = 'https://www.xcl.ink'
s.license = { :file => '../LICENSE' }
s.author = { '田梓萱' => 'zixuanxcl@gmail.com' }
s.source = { :path => '.' }
# This will ensure the source files in Classes/ are included in the native
# builds of apps using this FFI plugin. Podspec does not support relative
# paths, so Classes contains a forwarder C file that relatively imports
# `../src/*` so that the C sources can be shared among all target platforms.
s.source_files = 'Classes/**/*'
s.public_header_files = 'Classes**/*.h'
s.dependency 'Flutter'
s.platform = :ios, '9.0'
# Flutter.framework does not contain a i386 slice.
s.xcconfig = {
'CLANG_CXX_LANGUAGE_STANDARD' => 'c++20',
}
s.library = 'c++'
s.pod_target_xcconfig = {
'DEFINES_MODULE' => 'YES',
'EXCLUDED_ARCHS[sdk=iphonesimulator*]' => 'i386',
}
s.swift_version = '5.0'
end