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libraries/audio-tools/examples/examples-audiokit/streams-audiokit-tf/README.md

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+## Using the AI Thinker ESP32 Audio Kit Micro Speech
+
+I found some cheap [AI Thinker ESP32 Audio Kit V2.2](https://docs.ai-thinker.com/en/esp32-audio-kit) on AliExpress and because I was tired of all the wires I had to connect to implement my different scenarios that are possible with my [Arduino Audio Tools Library](https://github.com/pschatzmann/arduino-audio-tools), I thought it to be a good idea to buy this board.
+
+<img src="https://pschatzmann.github.io/Resources/img/audio-toolkit.png" alt="Audio Kit" />
+
+You dont need to bother about any wires because everything is on one nice board. Just just need to install the dependencies
+
+The staring point for doing speech recognition on an Arduino based board is TensorFlow Light For Microcontrollers with the example sketch called micro_speech!
+
+I have adapted the MicroSpeech example from TensorFlow Lite to follow the philosophy of this framework. The example uses a Tensorflow model which can recognise the words 'yes' and 'no'. The output stream class is TfLiteAudioOutput. In the example I am using an ESP32 AudioKit board, but you can replace this with any type of processor with a microphone.
+Further information can be found in the [Wiki](https://github.com/pschatzmann/arduino-audio-tools/wiki/TensorFlow-Lite---MicroSpeech)
+
+
+### Note
+
+The log level has been set to Info to help you to identify any problems. Please change it to AudioLogger::Warning to get the best sound quality!
+
+
+## Dependencies
+
+You need to install the following libraries:
+
+- https://github.com/pschatzmann/arduino-audio-tools
+- https://github.com/pschatzmann/arduino-audio-driver
+- https://github.com/pschatzmann/tflite-micro-arduino-examples

libraries/audio-tools/examples/examples-audiokit/streams-audiokit-tf/streams-audiokit-tf.ino

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+
+#include "AudioTools.h"
+#include "AudioTools/AudioLibs/AudioBoardStream.h"
+#include "AudioTools/AudioLibs/TfLiteAudioStream.h"
+#include "model.h"  // tensorflow model
+
+AudioBoardStream kit(AudioKitEs8388V1);  // Audio source
+TfLiteAudioStream tfl;  // Audio sink
+const char* kCategoryLabels[4] = {
+    "silence",
+    "unknown",
+    "yes",
+    "no",
+};
+StreamCopy copier(tfl, kit);  // copy mic to tfl
+int channels = 1;
+int samples_per_second = 16000;
+
+void respondToCommand(const char* found_command, uint8_t score,
+                      bool is_new_command) {
+  if (is_new_command) {
+    char buffer[80];
+    sprintf(buffer, "Result: %s, score: %d, is_new: %s", found_command, score,
+            is_new_command ? "true" : "false");
+    Serial.println(buffer);
+  }
+}
+
+void setup() {
+  Serial.begin(115200);
+  AudioToolsLogger.begin(Serial, AudioToolsLogLevel::Warning);
+
+  // setup Audiokit
+  auto cfg = kit.defaultConfig(RX_MODE);
+  cfg.input_device = ADC_INPUT_LINE2;
+  cfg.channels = channels;
+  cfg.sample_rate = samples_per_second;
+  cfg.use_apll = false;
+  //cfg.auto_clear = true;
+  cfg.buffer_size = 512;
+  cfg.buffer_count = 16;
+  kit.begin(cfg);
+
+  // Setup tensorflow
+  auto tcfg = tfl.defaultConfig();
+  tcfg.setCategories(kCategoryLabels);
+  tcfg.channels = channels;
+  tcfg.sample_rate = samples_per_second;
+  tcfg.kTensorArenaSize = 10 * 1024;
+  tcfg.respondToCommand = respondToCommand;
+  tcfg.model = g_model;
+  tfl.begin(tcfg);
+}
+
+void loop() { copier.copy(); }