Use a separate thread to initialize models for lazarus examples.

.github/workflows/lazarus.yaml

@@ -5,6 +5,7 @@ on:
     branches:
       - master
       - lazarus
+      - fix-lazarus
     paths:
       - '.github/workflows/lazarus.yaml'
       - 'CMakeLists.txt'

lazarus-examples/generate_subtitles/generate_subtitles.lpi

@@ -160,6 +160,10 @@
         <Filename Value="my_worker.pas"/>
         <IsPartOfProject Value="True"/>
       </Unit>
+      <Unit>
+        <Filename Value="my_init.pas"/>
+        <IsPartOfProject Value="True"/>
+      </Unit>
     </Units>
   </ProjectOptions>
   <CompilerOptions>

lazarus-examples/generate_subtitles/generate_subtitles.lpr

@@ -11,7 +11,7 @@
   athreads,
   {$ENDIF}
   Interfaces, // this includes the LCL widgetset
-  Forms, unit1, my_worker
+  Forms, unit1, my_worker, my_init
   { you can add units after this };
 
 {$R *.res}

lazarus-examples/generate_subtitles/my_init.pas

@@ -0,0 +1,358 @@
+unit my_init;
+
+{$mode ObjFPC}{$H+}
+
+interface
+
+uses
+  {$IFDEF UNIX}
+  cthreads,
+  cmem,
+  {$ENDIF}
+  {$IFDEF HASAMIGA}
+  athreads,
+  {$ENDIF}
+  Classes, SysUtils;
+
+type
+  TMyInitThread = class(TThread)
+  private
+    Status: AnsiString;
+    ModelDir: AnsiString;
+    procedure ShowStatus;
+
+  protected
+    procedure Execute; override;
+  public
+    Constructor Create(CreateSuspended: Boolean; ModelDirectory: AnsiString);
+  end;
+
+var
+  MyInitThread: TMyInitThread;
+
+implementation
+
+uses
+  unit1, sherpa_onnx;
+
+function CreateVad(VadFilename: AnsiString): TSherpaOnnxVoiceActivityDetector;
+var
+  Config: TSherpaOnnxVadModelConfig;
+
+  SampleRate: Integer;
+  WindowSize: Integer;
+begin
+  Initialize(Config);
+
+  SampleRate := 16000; {Please don't change it unless you know the details}
+  WindowSize := 512; {Please don't change it unless you know the details}
+
+  Config.SileroVad.Model := VadFilename;
+  Config.SileroVad.MinSpeechDuration := 0.5;
+  Config.SileroVad.MinSilenceDuration := 0.5;
+  Config.SileroVad.Threshold := 0.5;
+  Config.SileroVad.WindowSize := WindowSize;
+  Config.NumThreads:= 2;
+  Config.Debug:= True;
+  Config.Provider:= 'cpu';
+  Config.SampleRate := SampleRate;
+
+  Result := TSherpaOnnxVoiceActivityDetector.Create(Config, 30);
+end;
+
+function CreateOfflineRecognizerTransducer(
+  Tokens: AnsiString;
+  Encoder: AnsiString;
+  Decoder: AnsiString;
+  Joiner: AnsiString;
+  ModelType: AnsiString): TSherpaOnnxOfflineRecognizer;
+var
+  Config: TSherpaOnnxOfflineRecognizerConfig;
+begin
+  Initialize(Config);
+
+  Config.ModelConfig.Transducer.Encoder := Encoder;
+  Config.ModelConfig.Transducer.Decoder := Decoder;
+  Config.ModelConfig.Transducer.Joiner := Joiner;
+
+  Config.ModelConfig.ModelType := ModelType;
+  Config.ModelConfig.Tokens := Tokens;
+  Config.ModelConfig.Provider := 'cpu';
+  Config.ModelConfig.NumThreads := 2;
+  Config.ModelConfig.Debug := False;
+
+  Result := TSherpaOnnxOfflineRecognizer.Create(Config);
+end;
+
+function CreateOfflineRecognizerTeleSpeech(
+  Tokens: AnsiString;
+  TeleSpeech: AnsiString): TSherpaOnnxOfflineRecognizer;
+var
+  Config: TSherpaOnnxOfflineRecognizerConfig;
+begin
+  Initialize(Config);
+
+  Config.ModelConfig.TeleSpeechCtc := TeleSpeech;
+
+  Config.ModelConfig.Tokens := Tokens;
+  Config.ModelConfig.Provider := 'cpu';
+  Config.ModelConfig.NumThreads := 2;
+  Config.ModelConfig.Debug := False;
+
+  Result := TSherpaOnnxOfflineRecognizer.Create(Config);
+end;
+
+function CreateOfflineRecognizerParaformer(
+  Tokens: AnsiString;
+  Paraformer: AnsiString): TSherpaOnnxOfflineRecognizer;
+var
+  Config: TSherpaOnnxOfflineRecognizerConfig;
+begin
+  Initialize(Config);
+
+  Config.ModelConfig.Paraformer.Model := Paraformer;
+
+  Config.ModelConfig.Tokens := Tokens;
+  Config.ModelConfig.Provider := 'cpu';
+  Config.ModelConfig.NumThreads := 2;
+  Config.ModelConfig.Debug := False;
+
+  Result := TSherpaOnnxOfflineRecognizer.Create(Config);
+end;
+
+function CreateOfflineRecognizerSenseVoice(
+  Tokens: AnsiString;
+  SenseVoice: AnsiString): TSherpaOnnxOfflineRecognizer;
+var
+  Config: TSherpaOnnxOfflineRecognizerConfig;
+begin
+  Initialize(Config);
+
+  Config.ModelConfig.SenseVoice.Model := SenseVoice;
+  Config.ModelConfig.SenseVoice.Language := 'auto';
+  Config.ModelConfig.SenseVoice.UseItn := True;
+  Config.ModelConfig.Tokens := Tokens;
+  Config.ModelConfig.Provider := 'cpu';
+  Config.ModelConfig.NumThreads := 2;
+  Config.ModelConfig.Debug := False;
+
+  Result := TSherpaOnnxOfflineRecognizer.Create(Config);
+end;
+
+function CreateOfflineRecognizerWhisper(
+  Tokens: AnsiString;
+  WhisperEncoder: AnsiString;
+  WhisperDecoder: AnsiString): TSherpaOnnxOfflineRecognizer;
+var
+  Config: TSherpaOnnxOfflineRecognizerConfig;
+begin
+  Initialize(Config);
+
+  Config.ModelConfig.Whisper.Encoder := WhisperEncoder;
+  Config.ModelConfig.Whisper.Decoder := WhisperDecoder;
+  Config.ModelConfig.Tokens := Tokens;
+  Config.ModelConfig.Provider := 'cpu';
+  Config.ModelConfig.NumThreads := 2;
+  Config.ModelConfig.Debug := False;
+
+  Result := TSherpaOnnxOfflineRecognizer.Create(Config);
+end;
+
+constructor TMyInitThread.Create(CreateSuspended : boolean; ModelDirectory: AnsiString);
+begin
+  inherited Create(CreateSuspended);
+  ModelDir := ModelDirectory;
+  FreeOnTerminate := True;
+end;
+
+procedure TMyInitThread.ShowStatus;
+begin
+  Form1.UpdateInitStatus(Status);
+end;
+
+procedure TMyInitThread.Execute;
+var
+  Msg: AnsiString;
+  VadFilename: AnsiString;
+  Tokens: AnsiString;
+
+  WhisperEncoder: AnsiString;
+  WhisperDecoder: AnsiString;
+
+  SenseVoice: AnsiString;
+
+  Paraformer: AnsiString;
+
+  TeleSpeech: AnsiString;
+
+  TransducerEncoder: AnsiString; // from icefall
+  TransducerDecoder: AnsiString;
+  TransducerJoiner: AnsiString;
+
+  NeMoTransducerEncoder: AnsiString;
+  NeMoTransducerDecoder: AnsiString;
+  NeMoTransducerJoiner: AnsiString;
+begin
+    VadFilename := ModelDir + 'silero_vad.onnx';
+    Tokens := ModelDir + 'tokens.txt';
+
+    {
+      Please refer to
+      https://k2-fsa.github.io/sherpa/onnx/pretrained_models/whisper/export-onnx.html#available-models
+      for a list of whisper models.
+
+      In the code, we use the normalized filename whisper-encoder.onnx, whisper-decoder.onnx, and tokens.txt
+      You need to rename the existing model files.
+
+      For instance, if you use sherpa-onnx-whisper-tiny.en, you have to do
+        mv tiny.en-tokens.txt tokens.txt
+
+        mv tiny.en-encoder.onnx whisper-encoder.onnx
+        mv tiny.en-decoder.onnx whisper-decoder.onnx
+
+        // or use the int8.onnx
+
+        mv tiny.en-encoder.int8.onnx whisper-encoder.onnx
+        mv tiny.en-decoder.int8.onnx whisper-decoder.onnx
+    }
+    WhisperEncoder := ModelDir + 'whisper-encoder.onnx';
+    WhisperDecoder := ModelDir + 'whisper-decoder.onnx';
+
+
+    {
+      Please refer to
+      https://k2-fsa.github.io/sherpa/onnx/sense-voice/pretrained.html#pre-trained-models
+      to download models for SenseVoice.
+
+      In the code, we use the normalized model name sense-voice.onnx. You have
+      to rename the downloaded model files.
+
+      For example, you need to use
+
+          mv model.onnx sense-voice.onnx
+
+          // or use the int8.onnx
+          mv model.int8.onnx sense-voice.onnx
+    }
+
+    SenseVoice := ModelDir + 'sense-voice.onnx';
+
+    {
+      Please refer to
+      https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-paraformer/index.html
+      to download paraformer models.
+
+      Note that you have to rename model.onnx or model.int8.onnx to paraformer.onnx.
+      An example is given below for the rename:
+
+        cp model.onnx paraformer.onnx
+
+        // or use int8.onnx
+        cp model.int8.onnx paraformer.onnx
+    }
+    Paraformer := ModelDir + 'paraformer.onnx';
+
+
+    {
+      please refer to
+      https://k2-fsa.github.io/sherpa/onnx/pretrained_models/telespeech/models.html
+      to download TeleSpeech models.
+
+      Note that you have to rename model files after downloading. The following
+      is an example
+
+         mv model.onnx telespeech.onnx
+
+         // or to use int8.onnx
+
+         mv model.int8.onnx telespeech.onnx
+    }
+
+    TeleSpeech := ModelDir + 'telespeech.onnx';
+
+
+    {
+      Please refer to
+      https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
+      to download an icefall offline transducer model. Note that you need to rename the
+      model files to transducer-encoder.onnx, transducer-decoder.onnx, and
+      transducer-joiner.onnx
+    }
+    TransducerEncoder := ModelDir + 'transducer-encoder.onnx';
+    TransducerDecoder := ModelDir + 'transducer-decoder.onnx';
+    TransducerJoiner := ModelDir + 'transducer-joiner.onnx';
+
+    {
+      Please visit
+      https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+      to donwload a NeMo transducer model.
+    }
+    NeMoTransducerEncoder := ModelDir + 'nemo-transducer-encoder.onnx';
+    NeMoTransducerDecoder := ModelDir + 'nemo-transducer-decoder.onnx';
+    NeMoTransducerJoiner := ModelDir + 'nemo-transducer-joiner.onnx';
+
+    if not FileExists(VadFilename) then
+      begin
+        Status := VadFilename + ' does not exist! Please download it from' +
+          sLineBreak + 'https://github.com/k2-fsa/sherpa-onnx/tree/asr-models';
+        Synchronize(@ShowStatus);
+        Exit;
+      end;
+
+    if Form1.Vad = nil then
+      begin
+        Form1.Vad := CreateVad(VadFilename);
+      end;
+
+    if not FileExists(Tokens) then
+      begin
+        Status := Tokens + ' not found. Please download a non-streaming ASR model first!';
+        Synchronize(@ShowStatus);
+        Exit;
+      end;
+
+    if FileExists(WhisperEncoder) and FileExists(WhisperDecoder) then
+      begin
+        Form1.OfflineRecognizer := CreateOfflineRecognizerWhisper(Tokens, WhisperEncoder, WhisperDecoder);
+        Msg := 'Whisper';
+      end
+    else if FileExists(SenseVoice) then
+      begin
+        Form1.OfflineRecognizer := CreateOfflineRecognizerSenseVoice(Tokens, SenseVoice);
+        Msg := 'SenseVoice';
+      end
+    else if FileExists(Paraformer) then
+      begin
+        Form1.OfflineRecognizer := CreateOfflineRecognizerParaformer(Tokens, Paraformer);
+        Msg := 'Paraformer';
+      end
+    else if FileExists(TeleSpeech) then
+      begin
+        Form1.OfflineRecognizer := CreateOfflineRecognizerTeleSpeech(Tokens, TeleSpeech);
+        Msg := 'TeleSpeech';
+      end
+    else if FileExists(TransducerEncoder) and FileExists(TransducerDecoder) and FileExists(TransducerJoiner) then
+        begin
+          Form1.OfflineRecognizer := CreateOfflineRecognizerTransducer(Tokens,
+            TransducerEncoder, TransducerDecoder, TransducerJoiner, 'transducer');
+          Msg := 'Zipformer transducer';
+        end
+    else if FileExists(NeMoTransducerEncoder) and FileExists(NeMoTransducerDecoder) and FileExists(NeMoTransducerJoiner) then
+        begin
+          Form1.OfflineRecognizer := CreateOfflineRecognizerTransducer(Tokens,
+            NeMoTransducerEncoder, NeMoTransducerDecoder, NeMoTransducerJoiner, 'nemo_transducer');
+          Msg := 'NeMo transducer';
+        end
+    else
+      begin
+        Status := 'Please download at least one non-streaming speech recognition model first.';
+        Synchronize(@ShowStatus);
+        Exit;
+      end;
+
+    Status := 'Congratulations! The ' + Msg + ' model is initialized succesfully!';
+    Synchronize(@ShowStatus);
+end;
+
+end.
+