feat: add stt c api example (#1156)

@@ -24,6 +24,9 @@ target_link_libraries(audio-tagging-c-api sherpa-onnx-c-api)
 add_executable(add-punctuation-c-api add-punctuation-c-api.c)
 target_link_libraries(add-punctuation-c-api sherpa-onnx-c-api)
 
+add_executable(offline-stt-c-api offline-stt-c-api.c)
+target_link_libraries(offline-stt-c-api sherpa-onnx-c-api)
+
 if(SHERPA_ONNX_HAS_ALSA)
   add_subdirectory(./asr-microphone-example)
 elseif((UNIX AND NOT APPLE) OR LINUX)

+// c-api-examples/offline-stt-c-api.c
+//
+// Copyright (c)  2024  Xiaomi Corporation
+
+// We assume you have pre-downloaded the whisper multi-lingual models
+// from https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+// An example command to download the "tiny" whisper model is given below:
+//
+// clang-format off
+//
+// wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.tar.bz2
+// tar xvf sherpa-onnx-whisper-tiny.tar.bz2
+// rm sherpa-onnx-whisper-tiny.tar.bz2
+//
+// clang-format on
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+
+#include "sherpa-onnx/c-api/c-api.h"
+
+int32_t main() {
+  // You can find more test waves from
+  // https://hf-mirror.com/spaces/k2-fsa/spoken-language-identification/tree/main/test_wavs
+  const char *wav_filename = "./sherpa-onnx-whisper-tiny/test_wavs/0.wav";
+  const char *encoder_filename = "sherpa-onnx-whisper-tiny/tiny-encoder.onnx";
+  const char *decoder_filename = "sherpa-onnx-whisper-tiny/tiny-decoder.onnx";
+  const char *tokens_filename = "sherpa-onnx-whisper-tiny/tiny-tokens.txt";
+  const char *language = "en";
+  const char *provider = "cpu";
+
+  const SherpaOnnxWave *wave = SherpaOnnxReadWave(wav_filename);
+  if (wave == NULL) {
+    fprintf(stderr, "Failed to read %s\n", wav_filename);
+    return -1;
+  }
+
+  // Whisper config
+  SherpaOnnxOfflineWhisperModelConfig whisper_config;
+  memset(&whisper_config, 0, sizeof(whisper_config));
+  whisper_config.decoder = decoder_filename;
+  whisper_config.encoder = encoder_filename;
+  whisper_config.language = language;
+  whisper_config.tail_paddings = 0;
+  whisper_config.task = "transcribe";
+
+  // Offline model config
+  SherpaOnnxOfflineModelConfig offline_model_config;
+  memset(&offline_model_config, 0, sizeof(offline_model_config));
+  offline_model_config.bpe_vocab = "";
+  offline_model_config.debug = 1;
+  offline_model_config.num_threads = 1;
+  offline_model_config.provider = provider;
+  offline_model_config.tokens = tokens_filename;
+  offline_model_config.whisper = whisper_config;
+  offline_model_config.sense_voice =
+      (SherpaOnnxOfflineSenseVoiceModelConfig){"", "", 0};
+
+  // Recognizer config
+  SherpaOnnxOfflineRecognizerConfig recognizer_config;
+  memset(&recognizer_config, 0, sizeof(recognizer_config));
+  recognizer_config.decoding_method = "greedy_search";
+  recognizer_config.feat_config = (SherpaOnnxFeatureConfig){16000, 512};
+  recognizer_config.model_config = offline_model_config;
+
+  SherpaOnnxOfflineRecognizer *recognizer =
+      CreateOfflineRecognizer(&recognizer_config);
+
+  SherpaOnnxOfflineStream *stream = CreateOfflineStream(recognizer);
+
+  AcceptWaveformOffline(stream, wave->sample_rate, wave->samples,
+                        wave->num_samples);
+  DecodeOfflineStream(recognizer, stream);
+  SherpaOnnxOfflineRecognizerResult *result = GetOfflineStreamResult(stream);
+
+  fprintf(stderr, "Decoded text: %s\n", result->text);
+
+  DestroyOfflineRecognizerResult(result);
+  DestroyOfflineStream(stream);
+  DestroyOfflineRecognizer(recognizer);
+  SherpaOnnxFreeWave(wave);
+
+  return 0;
+}