Implement context biasing with a Aho Corasick automata (#145)

* Implement context graph

* Modify the interface to support context biasing

* Support context biasing in modified beam search; add python wrapper

* Support context biasing in python api example

* Minor fixes

* Fix context graph

* Minor fixes

* Fix tests

* Fix style

* Fix style

* Fix comments

* Minor fixes

* Add missing header

* Replace std::shared_ptr with std::unique_ptr for effciency

* Build graph in constructor

* Fix comments

* Minor fixes

* Fix docs

sherpa-onnx/csrc/offline-recognizer.h

@@ -26,6 +26,7 @@ struct OfflineRecognizerConfig {
 
   std::string decoding_method = "greedy_search";
   int32_t max_active_paths = 4;
+  float context_score = 1.5;
   // only greedy_search is implemented
   // TODO(fangjun): Implement modified_beam_search
 
@@ -34,12 +35,13 @@ struct OfflineRecognizerConfig {
                           const OfflineModelConfig &model_config,
                           const OfflineLMConfig &lm_config,
                           const std::string &decoding_method,
-                          int32_t max_active_paths)
+                          int32_t max_active_paths, float context_score)
       : feat_config(feat_config),
         model_config(model_config),
         lm_config(lm_config),
         decoding_method(decoding_method),
-        max_active_paths(max_active_paths) {}
+        max_active_paths(max_active_paths),
+        context_score(context_score) {}
 
   void Register(ParseOptions *po);
   bool Validate() const;
@@ -58,6 +60,10 @@ class OfflineRecognizer {
   /// Create a stream for decoding.
   std::unique_ptr<OfflineStream> CreateStream() const;
 
+  /// Create a stream for decoding.
+  std::unique_ptr<OfflineStream> CreateStream(
+      const std::vector<std::vector<int32_t>> &context_list) const;
+
   /** Decode a single stream
    *
    * @param s The stream to decode.