Add context biasing for mobile

android/SherpaOnnx/app/src/main/java/com/k2fsa/sherpa/onnx/SherpaOnnx.kt

@@ -85,14 +85,17 @@ class SherpaOnnx(
         acceptWaveform(ptr, samples, sampleRate)
 
     fun inputFinished() = inputFinished(ptr)
-    fun reset(recreate: Boolean = false) = reset(ptr, recreate = recreate)
+    fun reset(recreate: Boolean = false, hotwords: String = "") = reset(ptr, recreate, hotwords)
     fun decode() = decode(ptr)
     fun isEndpoint(): Boolean = isEndpoint(ptr)
     fun isReady(): Boolean = isReady(ptr)
 
     val text: String
         get() = getText(ptr)
 
+    val tokens: Array<String>
+        get() = getTokens(ptr)
+
     private external fun delete(ptr: Long)
 
     private external fun new(
@@ -107,10 +110,11 @@ class SherpaOnnx(
     private external fun acceptWaveform(ptr: Long, samples: FloatArray, sampleRate: Int)
     private external fun inputFinished(ptr: Long)
     private external fun getText(ptr: Long): String
-    private external fun reset(ptr: Long, recreate: Boolean)
+    private external fun reset(ptr: Long, recreate: Boolean, hotwords: String)
     private external fun decode(ptr: Long)
     private external fun isEndpoint(ptr: Long): Boolean
     private external fun isReady(ptr: Long): Boolean
+    private external fun getTokens(ptr: Long): Array<String>
 
     companion object {
         init {

android/SherpaOnnx2Pass/app/src/main/java/com/k2fsa/sherpa/onnx/SherpaOnnx.kt

@@ -120,14 +120,17 @@ class SherpaOnnx(
         acceptWaveform(ptr, samples, sampleRate)
 
     fun inputFinished() = inputFinished(ptr)
-    fun reset(recreate: Boolean = false) = reset(ptr, recreate = recreate)
+    fun reset(recreate: Boolean = false, hotwords: String = "") = reset(ptr, recreate, hotwords)
     fun decode() = decode(ptr)
     fun isEndpoint(): Boolean = isEndpoint(ptr)
     fun isReady(): Boolean = isReady(ptr)
 
     val text: String
         get() = getText(ptr)
 
+    val tokens: Array<String>
+        get() = getTokens(ptr)    
+
     private external fun delete(ptr: Long)
 
     private external fun new(
@@ -142,10 +145,11 @@ class SherpaOnnx(
     private external fun acceptWaveform(ptr: Long, samples: FloatArray, sampleRate: Int)
     private external fun inputFinished(ptr: Long)
     private external fun getText(ptr: Long): String
-    private external fun reset(ptr: Long, recreate: Boolean)
+    private external fun reset(ptr: Long, recreate: Boolean, hotwords: String)
     private external fun decode(ptr: Long)
     private external fun isEndpoint(ptr: Long): Boolean
     private external fun isReady(ptr: Long): Boolean
+    private external fun getTokens(ptr: Long): Array<String>
 
     companion object {
         init {

sherpa-onnx/jni/jni.cc

@@ -76,11 +76,24 @@ class SherpaOnnx {
 
   bool IsReady() const { return recognizer_.IsReady(stream_.get()); }
 
-  void Reset(bool recreate) {
-    if (recreate) {
-      stream_ = recognizer_.CreateStream();
+  // If keywords is an empty string, it just recreates the decoding stream
+  // If keywords is not empty, it will create a new decoding stream with
+  // the given keywords appended to the default keywords.
+  void Reset(bool recreate, const std::string &keywords = {}) {
+    if (keywords.empty()) {
+      if (recreate) {
+        stream_ = recognizer_.CreateStream();
+      } else {
+        recognizer_.Reset(stream_.get());
+      }
     } else {
-      recognizer_.Reset(stream_.get());
+      auto stream = recognizer_.CreateStream(keywords);
+      // Set new keywords failed, the stream_ will not be updated.
+      if (stream != nullptr) {
+        stream_ = std::move(stream);
+      } else {
+        SHERPA_ONNX_LOGE("Failed to set keywords: %s", keywords.c_str());
+      }
     }
   }
 
@@ -1509,9 +1522,12 @@ JNIEXPORT void JNICALL Java_com_k2fsa_sherpa_onnx_SherpaOnnxOffline_delete(
 
 SHERPA_ONNX_EXTERN_C
 JNIEXPORT void JNICALL Java_com_k2fsa_sherpa_onnx_SherpaOnnx_reset(
-    JNIEnv *env, jobject /*obj*/, jlong ptr, jboolean recreate) {
+    JNIEnv *env, jobject /*obj*/,
+    jlong ptr, jboolean recreate, jstring keywords) {
   auto model = reinterpret_cast<sherpa_onnx::SherpaOnnx *>(ptr);
-  model->Reset(recreate);
+  const char *p_keywords = env->GetStringUTFChars(keywords, nullptr);
+  model->Reset(recreate, p_keywords);
+  env->ReleaseStringUTFChars(keywords, p_keywords);
 }
 
 SHERPA_ONNX_EXTERN_C

swift-api-examples/SherpaOnnx.swift

@@ -188,7 +188,7 @@ class SherpaOnnxOnlineRecongitionResult {
 class SherpaOnnxRecognizer {
   /// A pointer to the underlying counterpart in C
   let recognizer: OpaquePointer!
-  let stream: OpaquePointer!
+  var stream: OpaquePointer!
 
   /// Constructor taking a model config
   init(
@@ -237,8 +237,23 @@ class SherpaOnnxRecognizer {
 
   /// Reset the recognizer, which clears the neural network model state
   /// and the state for decoding.
-  func reset() {
-    Reset(recognizer, stream)
+  /// If hotwords is an empty string, it just recreates the decoding stream
+  /// If hotwords is not empty, it will create a new decoding stream with
+  /// the given hotWords appended to the default hotwords.
+  func reset(hotwords: String? = nil) {
+    guard let words = hotwords, !words.isEmpty else {
+        Reset(recognizer, stream)
+        return
+    }
+
+    words.withCString { cString in
+        let newStream = CreateOnlineStreamWithHotwords(recognizer, cString)
+        // lock while release and replace stream
+        objc_sync_enter(self)
+        DestroyOnlineStream(stream)
+        stream = newStream
+        objc_sync_exit(self)
+    }
   }
 
   /// Signal that no more audio samples would be available.