Add java api for hotwords (#319)

* Add java api

* support websocket

* Fix kotlin

@@ -53,6 +53,8 @@ data class OnlineRecognizerConfig(
     var enableEndpoint: Boolean = true,
     var decodingMethod: String = "greedy_search",
     var maxActivePaths: Int = 4,
+    var hotwordsFile: String = "",
+    var hotwordsScore: Float = 1.5f,
 )
 
 class SherpaOnnx(

-
 ENTRY_POINT = ./
 
 LIB_SRC_DIR := ../sherpa-onnx/java-api/src/com/k2fsa/sherpa/onnx
@@ -65,18 +64,22 @@ clean:
 	mkdir -p ./lib
 
 runfile:
+		java -cp ./lib/sherpaonnx.jar:build $(RUNJFLAGS)  DecodeFile test.wav
 
-		java -cp ./lib/sherpaonnx.jar:build $(RUNJFLAGS)  DecodeFile
+runhotwords:
+		java -cp ./lib/sherpaonnx.jar:build $(RUNJFLAGS)  DecodeFile hotwords.wav
 
 runmic:
-
 		java -cp ./lib/sherpaonnx.jar:build $(RUNJFLAGS)  DecodeMic
 
 runsrv:
-		java   -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar  $(RUNJFLAGS)  websocketsrv.AsrWebsocketServer ../build/lib/libsherpa-onnx-jni.so ./modeltest.cfg
+		java   -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar  $(RUNJFLAGS)  websocketsrv.AsrWebsocketServer $(shell pwd)/../build/lib/libsherpa-onnx-jni.so ./modeltest.cfg
 
 runclient:
-		java   -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar  $(RUNJFLAGS)  websocketsrv.AsrWebsocketClient ../build/lib/libsherpa-onnx-jni.so 127.0.0.1 8890 ./test.wav 32
+		java   -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar  $(RUNJFLAGS)  websocketsrv.AsrWebsocketClient $(shell pwd)/../build/lib/libsherpa-onnx-jni.so 127.0.0.1 8890 ./test.wav 32
+
+runclienthotwords:
+		java   -cp $(BUILD_DIR):lib/Java-WebSocket-1.5.3.jar:lib/slf4j-simple-1.7.25.jar:lib/slf4j-api-1.7.25.jar:../lib/sherpaonnx.jar  $(RUNJFLAGS)  websocketsrv.AsrWebsocketClient $(shell pwd)/../build/lib/libsherpa-onnx-jni.so 127.0.0.1 8890 ./hotwords.wav 32
 
 buildlib: $(LIB_FILES:.java=.class)
 

@@ -12,6 +12,8 @@ num_threads=4
 enable_endpoint_detection=true
 decoding_method=modified_beam_search
 max_active_paths=4
+hotwords_file=
+hotwords_score=1.5
 lm_model=
 lm_scale=0.5
 model_type=zipformer

@@ -36,6 +36,8 @@ if [ ! -d $repo ];then
 	git lfs pull --include "*.onnx"
 	ls -lh *.onnx
 	popd
+	ln -s $repo/test_wavs/0.wav hotwords.wav
+
 fi
 
 log $(pwd)
@@ -64,3 +66,9 @@ cd ../java-api-examples
 make all
 
 make runfile
+
+echo "礼 拜 二" > hotwords.txt
+
+sed -i 's/hotwords_file=/hotwords_file=hotwords.txt/g' modeltest.cfg
+
+make runhotwords

@@ -49,6 +49,8 @@ public class DecodeFile {
       float rule3MinUtteranceLength = 20F;
       String decodingMethod = "greedy_search";
       int maxActivePaths = 4;
+      String hotwordsFile = "";
+      float hotwordsScore = 1.5F;
       String lm_model = "";
       float lm_scale = 0.5F;
       String modelType = "zipformer";
@@ -69,6 +71,8 @@ public class DecodeFile {
               lm_model,
               lm_scale,
               maxActivePaths,
+              hotwordsFile,
+              hotwordsScore,
               modelType);
       streamObj = rcgOjb.createStream();
     } catch (Exception e) {
@@ -158,7 +162,7 @@ public class DecodeFile {
     try {
       String appDir = System.getProperty("user.dir");
       System.out.println("appdir=" + appDir);
-      String fileName = appDir + "/test.wav";
+      String fileName = appDir + "/" + args[0];
       String cfgPath = appDir + "/modeltest.cfg";
       String soPath = appDir + "/../build/lib/libsherpa-onnx-jni.so";
       OnlineRecognizer.setSoPath(soPath);

@@ -140,8 +140,6 @@ public class AsrWebsocketServer extends WebSocketServer {
     }
   }
 
- 
-
   public boolean streamQueueFind(WebSocket conn) {
     return streamQueue.contains(conn);
   }
@@ -151,16 +149,16 @@ public class AsrWebsocketServer extends WebSocketServer {
 
       rcgOjb = new OnlineRecognizer(cfgPath);
       // size of stream thread pool
-      int streamThreadNum = Integer.valueOf(cfgMap.get("stream_thread_num"));
+      int streamThreadNum = Integer.valueOf(cfgMap.getOrDefault("stream_thread_num", "16"));
       // size of decoder thread pool
-      int decoderThreadNum = Integer.valueOf(cfgMap.get("decoder_thread_num"));
+      int decoderThreadNum = Integer.valueOf(cfgMap.getOrDefault("decoder_thread_num", "16"));
 
       // time(ms) idle for decoder thread when no job
-      int decoderTimeIdle = Integer.valueOf(cfgMap.get("decoder_time_idle"));
+      int decoderTimeIdle = Integer.valueOf(cfgMap.getOrDefault("decoder_time_idle", "200"));
       // size of streams for parallel decoding
-      int parallelDecoderNum = Integer.valueOf(cfgMap.get("parallel_decoder_num"));
+      int parallelDecoderNum = Integer.valueOf(cfgMap.getOrDefault("parallel_decoder_num", "16"));
       // time(ms) out for connection data
-      int deocderTimeOut = Integer.valueOf(cfgMap.get("deocder_time_out"));
+      int deocderTimeOut = Integer.valueOf(cfgMap.getOrDefault("deocder_time_out", "30000"));
 
       // create stream threads
       for (int i = 0; i < streamThreadNum; i++) {
@@ -218,13 +216,13 @@ public class AsrWebsocketServer extends WebSocketServer {
 
     String soPath = args[0];
     String cfgPath = args[1];
- 
+
     OnlineRecognizer.setSoPath(soPath);
     logger.info("readProperties");
     Map<String, String> cfgMap = AsrWebsocketServer.readProperties(cfgPath);
-    int port = Integer.valueOf(cfgMap.get("port"));
+    int port = Integer.valueOf(cfgMap.getOrDefault("port", "8890"));
 
-    int connectionThreadNum = Integer.valueOf(cfgMap.get("connection_thread_num"));
+    int connectionThreadNum = Integer.valueOf(cfgMap.getOrDefault("connection_thread_num", "16"));
     AsrWebsocketServer s = new AsrWebsocketServer(port, connectionThreadNum);
     logger.info("initModelWithCfg");
     s.initModelWithCfg(cfgMap, cfgPath);

@@ -44,38 +44,48 @@ public class OnlineRecognizer {
   public OnlineRecognizer(String modelCfgPath) {
     Map<String, String> proMap = this.readProperties(modelCfgPath);
     try {
-      int sampleRate = Integer.parseInt(proMap.get("sample_rate").trim());
+      int sampleRate = Integer.parseInt(proMap.getOrDefault("sample_rate", "16000").trim());
       this.sampleRate = sampleRate;
       EndpointRule rule1 =
           new EndpointRule(
-              false, Float.parseFloat(proMap.get("rule1_min_trailing_silence").trim()), 0.0F);
+              false,
+              Float.parseFloat(proMap.getOrDefault("rule1_min_trailing_silence", "2.4").trim()),
+              0.0F);
       EndpointRule rule2 =
           new EndpointRule(
-              true, Float.parseFloat(proMap.get("rule2_min_trailing_silence").trim()), 0.0F);
+              true,
+              Float.parseFloat(proMap.getOrDefault("rule2_min_trailing_silence", "1.2").trim()),
+              0.0F);
       EndpointRule rule3 =
           new EndpointRule(
-              false, 0.0F, Float.parseFloat(proMap.get("rule3_min_utterance_length").trim()));
+              false,
+              0.0F,
+              Float.parseFloat(proMap.getOrDefault("rule3_min_utterance_length", "20").trim()));
       EndpointConfig endCfg = new EndpointConfig(rule1, rule2, rule3);
 
-      OnlineParaformerModelConfig modelParaCfg = new OnlineParaformerModelConfig(proMap.get("encoder").trim(), proMap.get("decoder").trim());
+      OnlineParaformerModelConfig modelParaCfg =
+          new OnlineParaformerModelConfig(
+              proMap.getOrDefault("encoder", "").trim(), proMap.getOrDefault("decoder", "").trim());
       OnlineTransducerModelConfig modelTranCfg =
           new OnlineTransducerModelConfig(
-              proMap.get("encoder").trim(),
-              proMap.get("decoder").trim(),
-              proMap.get("joiner").trim());
+              proMap.getOrDefault("encoder", "").trim(),
+              proMap.getOrDefault("decoder", "").trim(),
+              proMap.getOrDefault("joiner", "").trim());
       OnlineModelConfig modelCfg =
           new OnlineModelConfig(
-              proMap.get("tokens").trim(),
-              Integer.parseInt(proMap.get("num_threads").trim()),
+              proMap.getOrDefault("tokens", "").trim(),
+              Integer.parseInt(proMap.getOrDefault("num_threads", "4").trim()),
               false,
-              proMap.get("model_type").trim(),
+              proMap.getOrDefault("model_type", "zipformer").trim(),
               modelParaCfg,
               modelTranCfg);
       FeatureConfig featConfig =
-          new FeatureConfig(sampleRate, Integer.parseInt(proMap.get("feature_dim").trim()));
+          new FeatureConfig(
+              sampleRate, Integer.parseInt(proMap.getOrDefault("feature_dim", "80").trim()));
       OnlineLMConfig onlineLmConfig =
           new OnlineLMConfig(
-              proMap.get("lm_model").trim(), Float.parseFloat(proMap.get("lm_scale").trim()));
+              proMap.getOrDefault("lm_model", "").trim(),
+              Float.parseFloat(proMap.getOrDefault("lm_scale", "0.5").trim()));
 
       OnlineRecognizerConfig rcgCfg =
           new OnlineRecognizerConfig(
@@ -83,9 +93,11 @@ public class OnlineRecognizer {
               modelCfg,
               endCfg,
               onlineLmConfig,
-              Boolean.parseBoolean(proMap.get("enable_endpoint_detection").trim()),
-              proMap.get("decoding_method").trim(),
-              Integer.parseInt(proMap.get("max_active_paths").trim()));
+              Boolean.parseBoolean(proMap.getOrDefault("enable_endpoint_detection", "true").trim()),
+              proMap.getOrDefault("decoding_method", "modified_beam_search").trim(),
+              Integer.parseInt(proMap.getOrDefault("max_active_paths", "4").trim()),
+              proMap.getOrDefault("hotwords_file", "").trim(),
+              Float.parseFloat(proMap.getOrDefault("hotwords_score", "1.5").trim()));
       // create a new Recognizer, first parameter kept for android asset_manager ANDROID_API__ >= 9
       this.ptr = createOnlineRecognizer(new Object(), rcgCfg);
 
@@ -98,41 +110,49 @@ public class OnlineRecognizer {
   public OnlineRecognizer(Object assetManager, String modelCfgPath) {
     Map<String, String> proMap = this.readProperties(modelCfgPath);
     try {
-      int sampleRate = Integer.parseInt(proMap.get("sample_rate").trim());
+      int sampleRate = Integer.parseInt(proMap.getOrDefault("sample_rate", "16000").trim());
       this.sampleRate = sampleRate;
       EndpointRule rule1 =
           new EndpointRule(
-              false, Float.parseFloat(proMap.get("rule1_min_trailing_silence").trim()), 0.0F);
+              false,
+              Float.parseFloat(proMap.getOrDefault("rule1_min_trailing_silence", "2.4").trim()),
+              0.0F);
       EndpointRule rule2 =
           new EndpointRule(
-              true, Float.parseFloat(proMap.get("rule2_min_trailing_silence").trim()), 0.0F);
+              true,
+              Float.parseFloat(proMap.getOrDefault("rule2_min_trailing_silence", "1.2").trim()),
+              0.0F);
       EndpointRule rule3 =
           new EndpointRule(
-              false, 0.0F, Float.parseFloat(proMap.get("rule3_min_utterance_length").trim()));
+              false,
+              0.0F,
+              Float.parseFloat(proMap.getOrDefault("rule3_min_utterance_length", "20").trim()));
       EndpointConfig endCfg = new EndpointConfig(rule1, rule2, rule3);
       OnlineParaformerModelConfig modelParaCfg =
           new OnlineParaformerModelConfig(
-              proMap.get("encoder").trim(), proMap.get("decoder").trim());
+              proMap.getOrDefault("encoder", "").trim(), proMap.getOrDefault("decoder", "").trim());
       OnlineTransducerModelConfig modelTranCfg =
           new OnlineTransducerModelConfig(
-              proMap.get("encoder").trim(),
-              proMap.get("decoder").trim(),
-              proMap.get("joiner").trim());
+              proMap.getOrDefault("encoder", "").trim(),
+              proMap.getOrDefault("decoder", "").trim(),
+              proMap.getOrDefault("joiner", "").trim());
 
       OnlineModelConfig modelCfg =
           new OnlineModelConfig(
-              proMap.get("tokens").trim(),
-              Integer.parseInt(proMap.get("num_threads").trim()),
+              proMap.getOrDefault("tokens", "").trim(),
+              Integer.parseInt(proMap.getOrDefault("num_threads", "4").trim()),
               false,
-              proMap.get("model_type").trim(),
+              proMap.getOrDefault("model_type", "zipformer").trim(),
               modelParaCfg,
               modelTranCfg);
       FeatureConfig featConfig =
-          new FeatureConfig(sampleRate, Integer.parseInt(proMap.get("feature_dim").trim()));
+          new FeatureConfig(
+              sampleRate, Integer.parseInt(proMap.getOrDefault("feature_dim", "80").trim()));
 
       OnlineLMConfig onlineLmConfig =
           new OnlineLMConfig(
-              proMap.get("lm_model").trim(), Float.parseFloat(proMap.get("lm_scale").trim()));
+              proMap.getOrDefault("lm_model", "").trim(),
+              Float.parseFloat(proMap.getOrDefault("lm_scale", "0.5").trim()));
 
       OnlineRecognizerConfig rcgCfg =
           new OnlineRecognizerConfig(
@@ -140,9 +160,11 @@ public class OnlineRecognizer {
               modelCfg,
               endCfg,
               onlineLmConfig,
-              Boolean.parseBoolean(proMap.get("enable_endpoint_detection").trim()),
-              proMap.get("decoding_method").trim(),
-              Integer.parseInt(proMap.get("max_active_paths").trim()));
+              Boolean.parseBoolean(proMap.getOrDefault("enable_endpoint_detection", "true").trim()),
+              proMap.getOrDefault("decoding_method", "modified_beam_search").trim(),
+              Integer.parseInt(proMap.getOrDefault("max_active_paths", "4").trim()),
+              proMap.getOrDefault("hotwords_file", "").trim(),
+              Float.parseFloat(proMap.getOrDefault("hotwords_score", "1.5").trim()));
       // create a new Recognizer, first parameter kept for android asset_manager ANDROID_API__ >= 9
       this.ptr = createOnlineRecognizer(assetManager, rcgCfg);
 
@@ -168,6 +190,8 @@ public class OnlineRecognizer {
       String lm_model,
       float lm_scale,
       int maxActivePaths,
+      String hotwordsFile,
+      float hotwordsScore,
       String modelType) {
     this.sampleRate = sampleRate;
     EndpointRule rule1 = new EndpointRule(false, rule1MinTrailingSilence, 0.0F);
@@ -189,7 +213,9 @@ public class OnlineRecognizer {
             onlineLmConfig,
             enableEndpointDetection,
             decodingMethod,
-            maxActivePaths);
+            maxActivePaths,
+            hotwordsFile,
+            hotwordsScore);
     // create a new Recognizer, first parameter kept for android asset_manager ANDROID_API__ >= 9
     this.ptr = createOnlineRecognizer(new Object(), rcgCfg);
   }
@@ -211,7 +237,6 @@ public class OnlineRecognizer {
         String key = (String) en.nextElement();
         String Property = props.getProperty(key);
         proMap.put(key, Property);
-        // System.out.println(key+"="+Property);
       }
 
     } catch (Exception e) {

@@ -12,6 +12,8 @@ public class OnlineRecognizerConfig {
   private final boolean enableEndpoint;
   private final String decodingMethod;
   private final int maxActivePaths;
+  private final String hotwordsFile;
+  private final float hotwordsScore;
 
   public OnlineRecognizerConfig(
       FeatureConfig featConfig,
@@ -20,7 +22,9 @@ public class OnlineRecognizerConfig {
       OnlineLMConfig lmConfig,
       boolean enableEndpoint,
       String decodingMethod,
-      int maxActivePaths) {
+      int maxActivePaths,
+      String hotwordsFile,
+      float hotwordsScore) {
     this.featConfig = featConfig;
     this.modelConfig = modelConfig;
     this.endpointConfig = endpointConfig;
@@ -28,6 +32,8 @@ public class OnlineRecognizerConfig {
     this.enableEndpoint = enableEndpoint;
     this.decodingMethod = decodingMethod;
     this.maxActivePaths = maxActivePaths;
+    this.hotwordsFile = hotwordsFile;
+    this.hotwordsScore = hotwordsScore;
   }
 
   public OnlineLMConfig getLmConfig() {

@@ -125,6 +125,15 @@ static OnlineRecognizerConfig GetConfig(JNIEnv *env, jobject config) {
   fid = env->GetFieldID(cls, "maxActivePaths", "I");
   ans.max_active_paths = env->GetIntField(config, fid);
 
+  fid = env->GetFieldID(cls, "hotwordsFile", "Ljava/lang/String;");
+  s = (jstring)env->GetObjectField(config, fid);
+  p = env->GetStringUTFChars(s, nullptr);
+  ans.hotwords_file = p;
+  env->ReleaseStringUTFChars(s, p);
+
+  fid = env->GetFieldID(cls, "hotwordsScore", "F");
+  ans.hotwords_score = env->GetFloatField(config, fid);
+
   //---------- feat config ----------
   fid = env->GetFieldID(cls, "featConfig",
                         "Lcom/k2fsa/sherpa/onnx/FeatureConfig;");
@@ -293,6 +302,15 @@ static OfflineRecognizerConfig GetOfflineConfig(JNIEnv *env, jobject config) {
   fid = env->GetFieldID(cls, "maxActivePaths", "I");
   ans.max_active_paths = env->GetIntField(config, fid);
 
+  fid = env->GetFieldID(cls, "hotwordsFile", "Ljava/lang/String;");
+  s = (jstring)env->GetObjectField(config, fid);
+  p = env->GetStringUTFChars(s, nullptr);
+  ans.hotwords_file = p;
+  env->ReleaseStringUTFChars(s, p);
+
+  fid = env->GetFieldID(cls, "hotwordsScore", "F");
+  ans.hotwords_score = env->GetFloatField(config, fid);
+
   //---------- feat config ----------
   fid = env->GetFieldID(cls, "featConfig",
                         "Lcom/k2fsa/sherpa/onnx/FeatureConfig;");