EngineX-Iluvatar/enginex-mr_series-sherpa-onnx
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Use a separate thread to initialize models for lazarus examples. (#1270)

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So that the main thread is not blocked and the user interface is responsive.
This commit is contained in:
Fangjun Kuang
2024-08-18 14:59:48 +08:00
committed by GitHub
parent 8c087d9110
commit f93f0ca94d
7 changed files with 405 additions and 301 deletions
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1
.github/workflows/lazarus.yaml vendored
View File

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

4
lazarus-examples/generate_subtitles/generate_subtitles.lpi
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@@ -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>

2
lazarus-examples/generate_subtitles/generate_subtitles.lpr
View File

@@ -11,7 +11,7 @@ uses
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}

358
lazarus-examples/generate_subtitles/my_init.pas Normal file
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@@ -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.

333
lazarus-examples/generate_subtitles/unit1.pas
View File

@@ -41,6 +41,7 @@ type
StopTime: Single;
TotalDuration: Single);
procedure UpdateProgress(StopTime: Single; TotalDuration: Single);
procedure UpdateInitStatus(Status: AnsiString);
public
Vad: TSherpaOnnxVoiceActivityDetector;
OfflineRecognizer: TSherpaOnnxOfflineRecognizer;
@@ -52,7 +53,8 @@ var
implementation
uses
my_worker
my_worker,
my_init
{$IFDEF DARWIN}
,MacOSAll
,CocoaAll
@@ -76,128 +78,7 @@ begin
end;
{$ENDIF}
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;
{$R *.lfm}
@@ -256,7 +137,7 @@ end;
procedure TForm1.FormClose(Sender: TObject; var CloseAction: TCloseAction);
begin
if (MyWorkerThread <> nil) and not MyWorkerThread.Finished then
if (MyWorkerThread <> nil) and (not MyWorkerThread.Finished) then
begin
MyWorkerThread.Terminate;
MyWorkerThread.WaitFor;
@@ -310,29 +191,35 @@ begin
Form1.ResultMemo.Lines.Add(NewResult);
end;
procedure TForm1.UpdateInitStatus(Status: AnsiString);
begin
if EndsStr('model is initialized succesfully!', Status) then
begin
Form1.ResultMemo.Lines.Add(Status);
Form1.ResultMemo.Lines.Add('Please select a 16000Hz wave file to generate subtiles');
Form1.ResultMemo.Lines.Add('You can download some test wave files from https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models');
Form1.ResultMemo.Lines.Add('For instance:');
Form1.ResultMemo.Lines.Add(' Chinese test wave: https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav');
Form1.ResultMemo.Lines.Add(' English test wave: https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/Obama.wav');
FileNameEdt.Enabled := True;
SelectFileBtn.Enabled := True;
end
else
begin
ShowMessage(Status);
Form1.ResultMemo.Lines.Clear();
Form1.ResultMemo.Lines.Add('Please refer to');
Form1.ResultMemo.Lines.Add('https://k2-fsa.github.io/sherpa/onnx/lazarus/generate-subtitles.html#download-models');
Form1.ResultMemo.Lines.Add('for how to download models');
InitBtn.Enabled := True;
end;
end;
procedure TForm1.InitBtnClick(Sender: TObject);
var
Msg: AnsiString;
ModelDir: AnsiString;
VadFilename: AnsiString;
Tokens: AnsiString;
WhisperEncoder: AnsiString;
WhisperDecoder: AnsiString;
SenseVoice: AnsiString;
Paraformer: AnsiString;
TeleSpeech: AnsiString;
TransducerEncoder: AnsiString; // from icefall
TransducerDecoder: AnsiString;
TransducerJoiner: AnsiString;
NeMoTransducerEncoder: AnsiString;
NeMoTransducerDecoder: AnsiString;
NeMoTransducerJoiner: AnsiString;
begin
{$IFDEF DARWIN}
ModelDir := GetResourcesPath;
@@ -340,162 +227,10 @@ begin
ModelDir := './';
{$ENDIF}
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
ShowMessage(VadFilename + ' does not exist! Please download it from' +
sLineBreak + 'https://github.com/k2-fsa/sherpa-onnx/tree/asr-models'
);
Exit;
end;
Self.Vad := CreateVad(VadFilename);
if not FileExists(Tokens) then
begin
ShowMessage(Tokens + ' not found. Please download a non-streaming ASR model first!');
Exit;
end;
if FileExists(WhisperEncoder) and FileExists(WhisperDecoder) then
begin
OfflineRecognizer := CreateOfflineRecognizerWhisper(Tokens, WhisperEncoder, WhisperDecoder);
Msg := 'Whisper';
end
else if FileExists(SenseVoice) then
begin
OfflineRecognizer := CreateOfflineRecognizerSenseVoice(Tokens, SenseVoice);
Msg := 'SenseVoice';
end
else if FileExists(Paraformer) then
begin
OfflineRecognizer := CreateOfflineRecognizerParaformer(Tokens, Paraformer);
Msg := 'Paraformer';
end
else if FileExists(TeleSpeech) then
begin
OfflineRecognizer := CreateOfflineRecognizerTeleSpeech(Tokens, TeleSpeech);
Msg := 'TeleSpeech';
end
else if FileExists(TransducerEncoder) and FileExists(TransducerDecoder) and FileExists(TransducerJoiner) then
begin
OfflineRecognizer := CreateOfflineRecognizerTransducer(Tokens,
TransducerEncoder, TransducerDecoder, TransducerJoiner, 'transducer');
Msg := 'Zipformer transducer';
end
else if FileExists(NeMoTransducerEncoder) and FileExists(NeMoTransducerDecoder) and FileExists(NeMoTransducerJoiner) then
begin
OfflineRecognizer := CreateOfflineRecognizerTransducer(Tokens,
NeMoTransducerEncoder, NeMoTransducerDecoder, NeMoTransducerJoiner, 'nemo_transducer');
Msg := 'NeMo transducer';
end
else
begin
ShowMessage('Please download at least one non-streaming speech recognition model first.');
Exit;
end;
MessageDlg('Congrat! The ' + Msg + ' model is initialized succesfully!', mtInformation, [mbOk], 0);
FileNameEdt.Enabled := True;
SelectFileBtn.Enabled := True;
InitBtn.Enabled := False;
Form1.ResultMemo.Lines.Clear();
ResultMemo.Lines.Add('Initializing the model. Please wait...');
MyInitThread := TMyInitThread.Create(False, ModelDir);
InitBtn.Enabled := False;
end;
end.

2
sherpa-onnx/csrc/silero-vad-model-config.cc
View File

@@ -69,7 +69,7 @@ bool SileroVadModelConfig::Validate() const {
std::string SileroVadModelConfig::ToString() const {
std::ostringstream os;
os << "SilerVadModelConfig(";
os << "SileroVadModelConfig(";
os << "model=\"" << model << "\", ";
os << "threshold=" << threshold << ", ";
os << "min_silence_duration=" << min_silence_duration << ", ";

6
sherpa-onnx/pascal-api/sherpa_onnx.pas
View File

@@ -98,6 +98,7 @@ type
destructor Destroy; override;
procedure AcceptWaveform(Samples: array of Single; SampleRate: Integer);
procedure InputFinished;
property GetHandle: Pointer Read Handle;
end;
TSherpaOnnxOnlineRecognizer = class
@@ -116,6 +117,7 @@ type
function IsEndpoint(Stream: TSherpaOnnxOnlineStream): Boolean;
function GetResult(Stream: TSherpaOnnxOnlineStream): TSherpaOnnxOnlineRecognizerResult;
property Config: TSherpaOnnxOnlineRecognizerConfig Read _Config;
property GetHandle: Pointer Read Handle;
end;
TSherpaOnnxOfflineTransducerModelConfig = record
@@ -213,6 +215,7 @@ type
constructor Create(P: Pointer);
destructor Destroy; override;
procedure AcceptWaveform(Samples: array of Single; SampleRate: Integer);
property GetHandle: Pointer Read Handle;
end;
TSherpaOnnxOfflineRecognizer = class
@@ -226,6 +229,7 @@ type
procedure Decode(Stream: TSherpaOnnxOfflineStream);
function GetResult(Stream: TSherpaOnnxOfflineStream): TSherpaOnnxOfflineRecognizerResult;
property Config: TSherpaOnnxOfflineRecognizerConfig Read _Config;
property GetHandle: Pointer Read Handle;
end;
TSherpaOnnxSileroVadModelConfig = record
@@ -262,6 +266,7 @@ type
procedure Reset;
function Size: Integer;
function Head: Integer;
property GetHandle: Pointer Read Handle;
end;
TSherpaOnnxSpeechSegment = record
@@ -286,6 +291,7 @@ type
procedure Reset;
procedure Flush;
property Config: TSherpaOnnxVadModelConfig Read _Config;
property GetHandle: Pointer Read Handle;
end;
{ It supports reading a single channel wave with 16-bit encoded samples.