Use alsa to read microphone in speaker identification demo. (#605)

cmake/cmake_extension.py

@@ -167,6 +167,7 @@ class BuildExtension(build_ext):
         if enable_alsa():
             binaries += ["sherpa-onnx-alsa"]
             binaries += ["sherpa-onnx-offline-tts-play-alsa"]
+            binaries += ["sherpa-onnx-alsa-offline-speaker-identification"]
 
         if is_windows():
             binaries += ["kaldi-native-fbank-core.dll"]

setup.py

@@ -60,6 +60,7 @@ def get_binaries_to_install():
     if enable_alsa():
         binaries += ["sherpa-onnx-alsa"]
         binaries += ["sherpa-onnx-offline-tts-play-alsa"]
+        binaries += ["sherpa-onnx-alsa-offline-speaker-identification"]
 
     if is_windows():
         binaries += ["kaldi-native-fbank-core.dll"]

sherpa-onnx/csrc/CMakeLists.txt

@@ -231,10 +231,12 @@ endif()
 if(SHERPA_ONNX_HAS_ALSA AND SHERPA_ONNX_ENABLE_BINARY)
   add_executable(sherpa-onnx-alsa sherpa-onnx-alsa.cc alsa.cc)
   add_executable(sherpa-onnx-offline-tts-play-alsa sherpa-onnx-offline-tts-play-alsa.cc alsa-play.cc)
+  add_executable(sherpa-onnx-alsa-offline-speaker-identification sherpa-onnx-alsa-offline-speaker-identification.cc alsa.cc)
 
   set(exes
     sherpa-onnx-alsa
     sherpa-onnx-offline-tts-play-alsa
+    sherpa-onnx-alsa-offline-speaker-identification
   )
   foreach(exe IN LISTS exes)
     target_link_libraries(${exe} sherpa-onnx-core)

sherpa-onnx/csrc/sherpa-onnx-alsa-offline-speaker-identification.cc

@@ -0,0 +1,287 @@
+// sherpa-onnx/csrc/sherpa-onnx-alsa-offline-speaker-identification.cc
+//
+// Copyright (c)  2024  Xiaomi Corporation
+
+#include <signal.h>
+#include <stdio.h>
+#include <stdlib.h>
+
+#include <algorithm>
+#include <fstream>
+#include <mutex>  // NOLINT
+#include <sstream>
+#include <thread>  // NOLINT
+
+#include "sherpa-onnx/csrc/alsa.h"
+#include "sherpa-onnx/csrc/macros.h"
+#include "sherpa-onnx/csrc/microphone.h"
+#include "sherpa-onnx/csrc/speaker-embedding-extractor.h"
+#include "sherpa-onnx/csrc/speaker-embedding-manager.h"
+#include "sherpa-onnx/csrc/wave-reader.h"
+
+enum class State {
+  kIdle,
+  kRecording,
+  kComputing,
+};
+
+State state = State::kIdle;
+
+// true to stop the program and exit
+bool stop = false;
+
+std::vector<float> samples;
+std::mutex samples_mutex;
+
+static void DetectKeyPress() {
+  SHERPA_ONNX_LOGE("\nPress Enter to start");
+  int32_t key;
+  while (!stop && (key = getchar())) {
+    if (key != 0x0a) {
+      continue;
+    }
+
+    switch (state) {
+      case State::kIdle:
+        SHERPA_ONNX_LOGE("\nStart recording. Press Enter to stop recording");
+        state = State::kRecording;
+        {
+          std::lock_guard<std::mutex> lock(samples_mutex);
+          samples.clear();
+        }
+        break;
+      case State::kRecording:
+        SHERPA_ONNX_LOGE("\nStop recording. Computing ...");
+        state = State::kComputing;
+        break;
+      case State::kComputing:
+        break;
+    }
+  }
+}
+
+static void Record(const char *device_name, int32_t expected_sample_rate) {
+  sherpa_onnx::Alsa alsa(device_name);
+
+  if (alsa.GetExpectedSampleRate() != expected_sample_rate) {
+    fprintf(stderr, "sample rate: %d != %d\n", alsa.GetExpectedSampleRate(),
+            expected_sample_rate);
+    exit(-1);
+  }
+
+  int32_t chunk = 0.1 * alsa.GetActualSampleRate();
+  while (!stop) {
+    std::lock_guard<std::mutex> lock(samples_mutex);
+    const std::vector<float> &s = alsa.Read(chunk);
+    samples.insert(samples.end(), s.begin(), s.end());
+  }
+}
+
+static void Handler(int32_t sig) {
+  stop = true;
+  fprintf(stderr, "\nCaught Ctrl + C. Press Enter to exit\n");
+}
+
+static std::vector<std::vector<float>> ComputeEmbeddings(
+    const std::vector<std::string> &filenames,
+    sherpa_onnx::SpeakerEmbeddingExtractor *extractor) {
+  std::vector<std::vector<float>> embedding_list;
+  embedding_list.reserve(filenames.size());
+
+  for (const auto &f : filenames) {
+    int32_t sampling_rate = -1;
+
+    bool is_ok = false;
+    const std::vector<float> samples =
+        sherpa_onnx::ReadWave(f, &sampling_rate, &is_ok);
+
+    if (!is_ok) {
+      fprintf(stderr, "Failed to read %s\n", f.c_str());
+      exit(-1);
+    }
+
+    auto s = extractor->CreateStream();
+    s->AcceptWaveform(sampling_rate, samples.data(), samples.size());
+    s->InputFinished();
+    auto embedding = extractor->Compute(s.get());
+    embedding_list.push_back(embedding);
+  }
+  return embedding_list;
+}
+
+static std::unordered_map<std::string, std::vector<std::string>>
+ReadSpeakerFile(const std::string &filename) {
+  std::unordered_map<std::string, std::vector<std::string>> ans;
+
+  std::ifstream is(filename);
+  if (!is) {
+    fprintf(stderr, "Failed to open %s", filename.c_str());
+    exit(0);
+  }
+
+  std::string line;
+  std::string name;
+  std::string path;
+
+  while (std::getline(is, line)) {
+    std::istringstream iss(line);
+    name.clear();
+    path.clear();
+
+    iss >> name >> path;
+    if (!iss || !iss.eof() || name.empty() || path.empty()) {
+      fprintf(stderr, "Invalid line: %s\n", line.c_str());
+      exit(-1);
+    }
+    ans[name].push_back(path);
+  }
+
+  return ans;
+}
+
+int32_t main(int32_t argc, char *argv[]) {
+  signal(SIGINT, Handler);
+
+  const char *kUsageMessage = R"usage(
+This program shows how to use non-streaming speaker identification.
+Usage:
+
+(1) Prepare a text file containing speaker related files.
+
+Each line in the text file contains two columns. The first column is the
+speaker name, while the second column contains the wave file of the speaker.
+
+If the text file contains multiple wave files for the same speaker, then the
+embeddings of these files are averaged.
+
+An example text file is given below:
+
+    foo /path/to/a.wav
+    bar /path/to/b.wav
+    foo /path/to/c.wav
+    foobar /path/to/d.wav
+
+Each wave file should contain only a single channel; the sample format
+should be int16_t; the sample rate can be arbitrary.
+
+(2) Download a model for computing speaker embeddings
+
+Please visit
+https://github.com/k2-fsa/sherpa-onnx/releases/tag/speaker-recongition-models
+to download a model. An example is given below:
+
+    wget https://github.com/k2-fsa/sherpa-onnx/releases/download/speaker-recongition-models/wespeaker_zh_cnceleb_resnet34.onnx
+
+Note that `zh` means Chinese, while `en` means English.
+
+(3) Run it !
+
+  ./bin/sherpa-onnx-alsa-offline-speaker-identification \
+    --model=/path/to/your-model.onnx \
+    --speaker-file=/path/to/speaker.txt \
+    device_name
+
+The device name specifies which microphone to use in case there are several
+on your system. You can use
+
+  arecord -l
+
+to find all available microphones on your computer. For instance, if it outputs
+
+**** List of CAPTURE Hardware Devices ****
+card 3: UACDemoV10 [UACDemoV1.0], device 0: USB Audio [USB Audio]
+  Subdevices: 1/1
+  Subdevice #0: subdevice #0
+
+and if you want to select card 3 and the device 0 on that card, please use:
+  plughw:3,0
+as the device_name.
+
+)usage";
+
+  sherpa_onnx::ParseOptions po(kUsageMessage);
+  float threshold = 0.5;
+  std::string speaker_file;
+
+  po.Register("threshold", &threshold,
+              "Threshold for comparing embedding scores.");
+
+  po.Register("speaker-file", &speaker_file, "Path to speaker.txt");
+
+  sherpa_onnx::SpeakerEmbeddingExtractorConfig config;
+  config.Register(&po);
+
+  po.Read(argc, argv);
+  if (po.NumArgs() != 1) {
+    fprintf(stderr, "Please provide only 1 argument: the device name\n");
+    po.PrintUsage();
+    exit(EXIT_FAILURE);
+  }
+
+  fprintf(stderr, "%s\n", config.ToString().c_str());
+
+  if (!config.Validate()) {
+    fprintf(stderr, "Errors in config! Please use --help to view the usage.\n");
+    return -1;
+  }
+
+  SHERPA_ONNX_LOGE("\nCreating extractor ...");
+  sherpa_onnx::SpeakerEmbeddingExtractor extractor(config);
+  SHERPA_ONNX_LOGE("\nextractor created!");
+
+  sherpa_onnx::SpeakerEmbeddingManager manager(extractor.Dim());
+
+  auto name2files = ReadSpeakerFile(speaker_file);
+  for (const auto &p : name2files) {
+    SHERPA_ONNX_LOGE("\nProcessing speaker %s", p.first.c_str());
+    auto embedding_list = ComputeEmbeddings(p.second, &extractor);
+    manager.Add(p.first, embedding_list);
+  }
+
+  std::string device_name = po.GetArg(1);
+  fprintf(stderr, "Use recording device: %s\n", device_name.c_str());
+  int32_t sample_rate = 16000;
+
+  std::thread t(DetectKeyPress);
+  std::thread t2(Record, device_name.c_str(), sample_rate);
+
+  while (!stop) {
+    switch (state) {
+      case State::kIdle:
+        break;
+      case State::kRecording:
+        break;
+      case State::kComputing: {
+        std::vector<float> buf;
+        {
+          std::lock_guard<std::mutex> lock(samples_mutex);
+          buf = std::move(samples);
+        }
+
+        auto s = extractor.CreateStream();
+        s->AcceptWaveform(sample_rate, buf.data(), buf.size());
+        s->InputFinished();
+        auto embedding = extractor.Compute(s.get());
+        auto name = manager.Search(embedding.data(), threshold);
+
+        if (name.empty()) {
+          name = "--Unknown--";
+        }
+
+        SHERPA_ONNX_LOGE("\nDone!\nDetected speaker is: %s", name.c_str());
+
+        state = State::kIdle;
+        SHERPA_ONNX_LOGE("\nPress Enter to start");
+        break;
+      }
+    }
+
+    using namespace std::chrono_literals;
+    std::this_thread::sleep_for(20ms);  // sleep for 20ms
+  }
+
+  t.join();
+  t2.join();
+
+  return 0;
+}

sherpa-onnx/csrc/sherpa-onnx-alsa.cc

@@ -34,14 +34,14 @@ Usage:
     --provider=cpu \
     --num-threads=2 \
     --decoding-method=greedy_search \
-    device_name \
+    device_name
 
 Please refer to
 https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
 for a list of pre-trained models to download.
 
 The device name specifies which microphone to use in case there are several
-on you system. You can use
+on your system. You can use
 
   arecord -l