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Pascal API for VAD (#1249)

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This commit is contained in:
Fangjun Kuang
2024-08-13 16:16:51 +08:00
committed by GitHub
parent a7dc6c2c16
commit 619279b162
24 changed files with 1199 additions and 14 deletions
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2
pascal-api-examples/README.md
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@@ -8,3 +8,5 @@ APIs of [sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx).
|[read-wav](./read-wav)|It shows how to read a wave file.|
|[streaming-asr](./streaming-asr)| It shows how to use streaming models for speech recognition.|
|[non-streaming-asr](./non-streaming-asr)| It shows how to use non-streaming models for speech recognition.|
|[vad](./vad)| It shows how to use the voice activity detection API.|
|[vad-with-non-streaming-asr](./vad-with-non-streaming-asr)| It shows how to use the voice activity detection API with non-streaming models for speech recognition.|

2
pascal-api-examples/non-streaming-asr/nemo_ctc.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.NeMoCtC.Model := './sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/model.onnx';
Config.ModelConfig.Tokens := './sherpa-onnx-nemo-fast-conformer-ctc-be-de-en-es-fr-hr-it-pl-ru-uk-20k/tokens.txt';
Config.ModelConfig.Provider := 'cpu';

2
pascal-api-examples/non-streaming-asr/nemo_transducer.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.Transducer.Encoder := './sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/encoder.onnx';
Config.ModelConfig.Transducer.Decoder := './sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/decoder.onnx';
Config.ModelConfig.Transducer.Joiner := './sherpa-onnx-nemo-fast-conformer-transducer-be-de-en-es-fr-hr-it-pl-ru-uk-20k/joiner.onnx';

2
pascal-api-examples/non-streaming-asr/paraformer.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.Paraformer.Model := './sherpa-onnx-paraformer-zh-2023-09-14/model.int8.onnx';
Config.ModelConfig.Tokens := './sherpa-onnx-paraformer-zh-2023-09-14/tokens.txt';
Config.ModelConfig.Provider := 'cpu';

2
pascal-api-examples/non-streaming-asr/paraformer_itn.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.Paraformer.Model := './sherpa-onnx-paraformer-zh-2023-09-14/model.int8.onnx';
Config.ModelConfig.Tokens := './sherpa-onnx-paraformer-zh-2023-09-14/tokens.txt';
Config.ModelConfig.Provider := 'cpu';

2
pascal-api-examples/non-streaming-asr/sense_voice.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.SenseVoice.Model := './sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.int8.onnx';
Config.ModelConfig.SenseVoice.Language := 'auto';
Config.ModelConfig.SenseVoice.UseItn := False;

2
pascal-api-examples/non-streaming-asr/telespeech_ctc.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.TeleSpeechCtc := './sherpa-onnx-telespeech-ctc-int8-zh-2024-06-04/model.int8.onnx';
Config.ModelConfig.Tokens := './sherpa-onnx-telespeech-ctc-int8-zh-2024-06-04/tokens.txt';
Config.ModelConfig.Provider := 'cpu';

2
pascal-api-examples/non-streaming-asr/whisper.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.Whisper.Encoder := './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx';
Config.ModelConfig.Whisper.Decoder := './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx';
Config.ModelConfig.Tokens := './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt';

2
pascal-api-examples/non-streaming-asr/zipformer_transducer.pas
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@@ -33,6 +33,8 @@ var
Duration: Single;
RealTimeFactor: Single;
begin
Initialize(Config);
Config.ModelConfig.Transducer.Encoder := './sherpa-onnx-zipformer-gigaspeech-2023-12-12/encoder-epoch-30-avg-1.int8.onnx';
Config.ModelConfig.Transducer.Decoder := './sherpa-onnx-zipformer-gigaspeech-2023-12-12/decoder-epoch-30-avg-1.onnx';
Config.ModelConfig.Transducer.Joiner := './sherpa-onnx-zipformer-gigaspeech-2023-12-12/joiner-epoch-30-avg-1.onnx';

3
pascal-api-examples/vad-with-non-streaming-asr/.gitignore vendored Normal file
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@@ -0,0 +1,3 @@
!run-*.sh
vad_with_whisper
vad_with_sense_voice

12
pascal-api-examples/vad-with-non-streaming-asr/README.md Normal file
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@@ -0,0 +1,12 @@
# Introduction
This directory contains examples for how to use the VAD (voice activity detection)
with non-streaming speech recognition models.
|Directory| Description|
|---------|------------|
|[run-vad-with-whisper.sh](./run-vad-with-whisper.sh)|It shows how to use the VAD + Whisper for speech recognition.|
|[run-vad-with-sense-voice.sh](./run-vad-with-sense-voice.sh)|It shows how to use the VAD + SenseVoice for speech recognition.|
Please refer to [non-streaming-asr](../non-streaming-asr) for more kinds of non-streaming models.

48
pascal-api-examples/vad-with-non-streaming-asr/run-vad-with-sense-voice.sh Executable file
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@@ -0,0 +1,48 @@
#!/usr/bin/env bash
set -ex
SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
SHERPA_ONNX_DIR=$(cd $SCRIPT_DIR/../.. && pwd)
echo "SHERPA_ONNX_DIR: $SHERPA_ONNX_DIR"
if [[ ! -f ../../build/install/lib/libsherpa-onnx-c-api.dylib && ! -f ../../build/install/lib/libsherpa-onnx-c-api.so && ! -f ../../build/install/lib/sherpa-onnx-c-api.dll ]]; then
mkdir -p ../../build
pushd ../../build
cmake \
-DCMAKE_INSTALL_PREFIX=./install \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
..
cmake --build . --target install --config Release
popd
fi
if [[ ! -f ./silero_vad.onnx ]]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
fi
if [ ! -f ./lei-jun-test.wav ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
fi
if [ ! -f ./sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
tar xvf sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
rm sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17.tar.bz2
fi
fpc \
-Fu$SHERPA_ONNX_DIR/sherpa-onnx/pascal-api \
-Fl$SHERPA_ONNX_DIR/build/install/lib \
./vad_with_sense_voice.pas
export LD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$LD_LIBRARY_PATH
export DYLD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$DYLD_LIBRARY_PATH
./vad_with_sense_voice

49
pascal-api-examples/vad-with-non-streaming-asr/run-vad-with-whisper.sh Executable file
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@@ -0,0 +1,49 @@
#!/usr/bin/env bash
set -ex
SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
SHERPA_ONNX_DIR=$(cd $SCRIPT_DIR/../.. && pwd)
echo "SHERPA_ONNX_DIR: $SHERPA_ONNX_DIR"
if [[ ! -f ../../build/install/lib/libsherpa-onnx-c-api.dylib && ! -f ../../build/install/lib/libsherpa-onnx-c-api.so && ! -f ../../build/install/lib/sherpa-onnx-c-api.dll ]]; then
mkdir -p ../../build
pushd ../../build
cmake \
-DCMAKE_INSTALL_PREFIX=./install \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
..
cmake --build . --target install --config Release
popd
fi
if [[ ! -f ./silero_vad.onnx ]]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
fi
if [ ! -f ./Obama.wav ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/Obama.wav
fi
if [ ! -f ./sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.en.tar.bz2
tar xvf sherpa-onnx-whisper-tiny.en.tar.bz2
rm sherpa-onnx-whisper-tiny.en.tar.bz2
fi
fpc \
-Fu$SHERPA_ONNX_DIR/sherpa-onnx/pascal-api \
-Fl$SHERPA_ONNX_DIR/build/install/lib \
./vad_with_whisper.pas
export LD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$LD_LIBRARY_PATH
export DYLD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$DYLD_LIBRARY_PATH
./vad_with_whisper

137
pascal-api-examples/vad-with-non-streaming-asr/vad_with_sense_voice.pas Normal file
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@@ -0,0 +1,137 @@
{ Copyright (c) 2024 Xiaomi Corporation }
{
This file shows how to use a non-streaming SenseVoice model
with silero VAD to decode files.
You can download the model files from
https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
}
program vad_with_whisper;
{$mode objfpc}
uses
sherpa_onnx,
SysUtils;
function CreateVad(): 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 := './silero_vad.onnx';
Config.SileroVad.MinSpeechDuration := 0.5;
Config.SileroVad.MinSilenceDuration := 0.5;
Config.SileroVad.Threshold := 0.5;
Config.SileroVad.WindowSize := WindowSize;
Config.NumThreads:= 1;
Config.Debug:= True;
Config.Provider:= 'cpu';
Config.SampleRate := SampleRate;
Result := TSherpaOnnxVoiceActivityDetector.Create(Config, 30);
end;
function CreateOfflineRecognizer(): TSherpaOnnxOfflineRecognizer;
var
Config: TSherpaOnnxOfflineRecognizerConfig;
begin
Initialize(Config);
Config.ModelConfig.SenseVoice.Model := './sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/model.int8.onnx';
Config.ModelConfig.SenseVoice.Language := 'auto';
Config.ModelConfig.SenseVoice.UseItn := False;
Config.ModelConfig.Tokens := './sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17/tokens.txt';
Config.ModelConfig.Provider := 'cpu';
Config.ModelConfig.NumThreads := 1;
Config.ModelConfig.Debug := False;
Result := TSherpaOnnxOfflineRecognizer.Create(Config);
end;
var
Wave: TSherpaOnnxWave;
Recognizer: TSherpaOnnxOfflineRecognizer;
Vad: TSherpaOnnxVoiceActivityDetector;
Offset: Integer;
WindowSize: Integer;
SpeechSegment: TSherpaOnnxSpeechSegment;
Start: Single;
Duration: Single;
Stream: TSherpaOnnxOfflineStream;
RecognitionResult: TSherpaOnnxOfflineRecognizerResult;
begin
Vad := CreateVad();
Recognizer := CreateOfflineRecognizer();
Wave := SherpaOnnxReadWave('./lei-jun-test.wav');
if Wave.SampleRate <> Vad.Config.SampleRate then
begin
WriteLn(Format('Expected sample rate: %d. Given: %d',
[Vad.Config.SampleRate, Wave.SampleRate]));
Exit;
end;
WindowSize := Vad.Config.SileroVad.WindowSize;
Offset := 0;
while Offset + WindowSize <= Length(Wave.Samples) do
begin
Vad.AcceptWaveform(Wave.Samples, Offset, WindowSize);
Offset += WindowSize;
while not Vad.IsEmpty do
begin
SpeechSegment := Vad.Front();
Vad.Pop();
Stream := Recognizer.CreateStream();
Stream.AcceptWaveform(SpeechSegment.Samples, Wave.SampleRate);
Recognizer.Decode(Stream);
RecognitionResult := Recognizer.GetResult(Stream);
Start := SpeechSegment.Start / Wave.SampleRate;
Duration := Length(SpeechSegment.Samples) / Wave.SampleRate;
WriteLn(Format('%.3f -- %.3f %s',
[Start, Start + Duration, RecognitionResult.Text]));
FreeAndNil(Stream);
end;
end;
Vad.Flush;
while not Vad.IsEmpty do
begin
SpeechSegment := Vad.Front();
Vad.Pop();
Stream := Recognizer.CreateStream();
Stream.AcceptWaveform(SpeechSegment.Samples, Wave.SampleRate);
Recognizer.Decode(Stream);
RecognitionResult := Recognizer.GetResult(Stream);
Start := SpeechSegment.Start / Wave.SampleRate;
Duration := Length(SpeechSegment.Samples) / Wave.SampleRate;
WriteLn(Format('%.3f -- %.3f %s',
[Start, Start + Duration, RecognitionResult.Text]));
FreeAndNil(Stream);
end;
FreeAndNil(Recognizer);
FreeAndNil(Vad);
end.

136
pascal-api-examples/vad-with-non-streaming-asr/vad_with_whisper.pas Normal file
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@@ -0,0 +1,136 @@
{ Copyright (c) 2024 Xiaomi Corporation }
{
This file shows how to use a non-streaming Whisper model
with silero VAD to decode files.
You can download the model files from
https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
}
program vad_with_whisper;
{$mode objfpc}
uses
sherpa_onnx,
SysUtils;
function CreateVad(): 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 := './silero_vad.onnx';
Config.SileroVad.MinSpeechDuration := 0.5;
Config.SileroVad.MinSilenceDuration := 0.5;
Config.SileroVad.Threshold := 0.5;
Config.SileroVad.WindowSize := WindowSize;
Config.NumThreads:= 1;
Config.Debug:= True;
Config.Provider:= 'cpu';
Config.SampleRate := SampleRate;
Result := TSherpaOnnxVoiceActivityDetector.Create(Config, 30);
end;
function CreateOfflineRecognizer(): TSherpaOnnxOfflineRecognizer;
var
Config: TSherpaOnnxOfflineRecognizerConfig;
begin
Initialize(Config);
Config.ModelConfig.Whisper.Encoder := './sherpa-onnx-whisper-tiny.en/tiny.en-encoder.int8.onnx';
Config.ModelConfig.Whisper.Decoder := './sherpa-onnx-whisper-tiny.en/tiny.en-decoder.int8.onnx';
Config.ModelConfig.Tokens := './sherpa-onnx-whisper-tiny.en/tiny.en-tokens.txt';
Config.ModelConfig.Provider := 'cpu';
Config.ModelConfig.NumThreads := 1;
Config.ModelConfig.Debug := False;
Result := TSherpaOnnxOfflineRecognizer.Create(Config);
end;
var
Wave: TSherpaOnnxWave;
Recognizer: TSherpaOnnxOfflineRecognizer;
Vad: TSherpaOnnxVoiceActivityDetector;
Offset: Integer;
WindowSize: Integer;
SpeechSegment: TSherpaOnnxSpeechSegment;
Start: Single;
Duration: Single;
Stream: TSherpaOnnxOfflineStream;
RecognitionResult: TSherpaOnnxOfflineRecognizerResult;
begin
Vad := CreateVad();
Recognizer := CreateOfflineRecognizer();
Wave := SherpaOnnxReadWave('./Obama.wav');
if Wave.SampleRate <> Vad.Config.SampleRate then
begin
WriteLn(Format('Expected sample rate: %d. Given: %d',
[Vad.Config.SampleRate, Wave.SampleRate]));
Exit;
end;
WindowSize := Vad.Config.SileroVad.WindowSize;
Offset := 0;
while Offset + WindowSize <= Length(Wave.Samples) do
begin
Vad.AcceptWaveform(Wave.Samples, Offset, WindowSize);
Offset += WindowSize;
while not Vad.IsEmpty do
begin
SpeechSegment := Vad.Front();
Vad.Pop();
Stream := Recognizer.CreateStream();
Stream.AcceptWaveform(SpeechSegment.Samples, Wave.SampleRate);
Recognizer.Decode(Stream);
RecognitionResult := Recognizer.GetResult(Stream);
Start := SpeechSegment.Start / Wave.SampleRate;
Duration := Length(SpeechSegment.Samples) / Wave.SampleRate;
WriteLn(Format('%.3f -- %.3f %s',
[Start, Start + Duration, RecognitionResult.Text]));
FreeAndNil(Stream);
end;
end;
Vad.Flush;
while not Vad.IsEmpty do
begin
SpeechSegment := Vad.Front();
Vad.Pop();
Stream := Recognizer.CreateStream();
Stream.AcceptWaveform(SpeechSegment.Samples, Wave.SampleRate);
Recognizer.Decode(Stream);
RecognitionResult := Recognizer.GetResult(Stream);
Start := SpeechSegment.Start / Wave.SampleRate;
Duration := Length(SpeechSegment.Samples) / Wave.SampleRate;
WriteLn(Format('%.3f -- %.3f %s',
[Start, Start + Duration, RecognitionResult.Text]));
FreeAndNil(Stream);
end;
FreeAndNil(Recognizer);
FreeAndNil(Vad);
end.

3
pascal-api-examples/vad/.gitignore vendored Normal file
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@@ -0,0 +1,3 @@
!run*.sh
circular_buffer
remove_silence

11
pascal-api-examples/vad/README.md Normal file
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@@ -0,0 +1,11 @@
# Introduction
This directory contains examples for how to use the VAD (voice activity detection)
APIs.
|Directory| Description|
|---------|------------|
|[run-circular-buffer.sh](./run-circular-buffer.sh)|It shows how to use the circular buffer API.|
|[run-remove-silence.sh](./run-remove-silence.sh)|It shows how to use the VAD API to remove silences from a wave file.|

106
pascal-api-examples/vad/circular_buffer.pas Normal file
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@@ -0,0 +1,106 @@
{ Copyright (c) 2024 Xiaomi Corporation }
program circular_buffer;
{
This file shows how to use the CircularBuffer API of sherpa-onnx
}
{$mode objfpc}
{$ASSERTIONS ON}
uses
sherpa_onnx;
var
Buffer: TSherpaOnnxCircularBuffer;
Samples: TSherpaOnnxSamplesArray;
begin
{The initial capacity is 5. It will be resized automatically if needed.}
Buffer := TSherpaOnnxCircularBuffer.Create(5);
Assert(Buffer.Size = 0);
Assert(Buffer.Head = 0);
Buffer.Push([0, 10, 20]);
{Push() changes Size. Head is not changed.}
Assert(Buffer.Size = 3);
Assert(Buffer.Head = 0);
Samples := Buffer.Get(0, 1);
Assert(Length(Samples) = 1);
Assert(Samples[0] = 0);
{ Get() does not change Size or Head}
Assert(Buffer.Size = 3);
Assert(Buffer.Head = 0);
Samples := Buffer.Get(0, 2);
Assert(Length(Samples) = 2);
Assert(Samples[0] = 0);
Assert(Samples[1] = 10);
{ The buffer will be resized since its initial capacity is 5 but we have
pushed 7 elements into it.
No data is lost during the resize.
}
Buffer.Push([30, 40, 50, 60]);
Assert(Buffer.Size = 7); {There are now 7 elements}
Assert(Buffer.Head = 0);
{Remove the first 4 elements}
Buffer.Pop(4);
Assert(Buffer.Size = 3); {There are only 3 elements left}
Assert(Buffer.Head = 4);
Samples := Buffer.Get(Buffer.Head, 2);
Assert(Length(Samples) = 2);
Assert(Samples[0] = 40);
Assert(Samples[1] = 50);
Buffer.Pop(1);
Assert(Buffer.Size = 2); {There are only 2 elements left}
Assert(Buffer.Head = 5);
Samples := Buffer.Get(Buffer.Head, 2);
Assert(Length(Samples) = 2);
Assert(Samples[0] = 50);
Assert(Samples[1] = 60);
Buffer.Pop(2);
Assert(Buffer.Size = 0); {There are no elements left}
Assert(Buffer.Head = 7);
Buffer.Push([100, 200, 300, 400, 500]);
Assert(Buffer.Size = 5);
Assert(Buffer.Head = 7);
Buffer.Pop(4);
Assert(Buffer.Size = 1);
{Head can be larger than the Capacity!
This is what circular means. It points to Buffer.Head / Capacity.
}
Assert(Buffer.Head = 11);
Buffer.Push([600, 700]);
Assert(Buffer.Size = 3);
Assert(Buffer.Head = 11);
Samples := Buffer.Get(Buffer.Head, 3);
Assert(Length(Samples) = 3);
Assert(Samples[0] = 500);
Assert(Samples[1] = 600);
Assert(Samples[2] = 700);
Buffer.Pop(3);
Assert(Buffer.Size = 0);
Assert(Buffer.Head = 14);
Buffer.Reset();
Assert(Buffer.Size = 0);
Assert(Buffer.Head = 0);
end.

115
pascal-api-examples/vad/remove_silence.pas Normal file
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@@ -0,0 +1,115 @@
{ Copyright (c) 2024 Xiaomi Corporation }
{
This file shows how to use the VAD API from sherpa-onnx
to remove silences from a wave file.
}
program main;
{$mode delphi}
uses
sherpa_onnx,
SysUtils;
var
Wave: TSherpaOnnxWave;
Config: TSherpaOnnxVadModelConfig;
Vad: TSherpaOnnxVoiceActivityDetector;
Offset: Integer;
WindowSize: Integer;
SpeechSegment: TSherpaOnnxSpeechSegment;
Start: Single;
Duration: Single;
SampleRate: Integer;
AllSpeechSegment: array of TSherpaOnnxSpeechSegment;
AllSamples: array of Single;
N: Integer;
I: Integer;
begin
SampleRate := 16000; {Please don't change it unless you know the details}
Wave := SherpaOnnxReadWave('./lei-jun-test.wav');
if Wave.SampleRate <> SampleRate then
begin
WriteLn(Format('Expected sample rate: %d. Given: %d',
[SampleRate, Wave.SampleRate]));
Exit;
end;
WindowSize := 512; {Please don't change it unless you know the details}
Initialize(Config);
Config.SileroVad.Model := './silero_vad.onnx';
Config.SileroVad.MinSpeechDuration := 0.25;
Config.SileroVad.MinSilenceDuration := 0.5;
Config.SileroVad.Threshold := 0.5;
Config.SileroVad.WindowSize := WindowSize;
Config.NumThreads:= 1;
Config.Debug:= True;
Config.Provider:= 'cpu';
Config.SampleRate := SampleRate;
Vad := TSherpaOnnxVoiceActivityDetector.Create(Config, 20);
AllSpeechSegment := nil;
AllSamples := nil;
Offset := 0;
while Offset + WindowSize <= Length(Wave.Samples) do
begin
Vad.AcceptWaveform(Wave.Samples, Offset, WindowSize);
Inc(Offset, WindowSize);
while not Vad.IsEmpty do
begin
SetLength(AllSpeechSegment, Length(AllSpeechSegment) + 1);
SpeechSegment := Vad.Front();
Vad.Pop();
AllSpeechSegment[Length(AllSpeechSegment)-1] := SpeechSegment;
Start := SpeechSegment.Start / SampleRate;
Duration := Length(SpeechSegment.Samples) / SampleRate;
WriteLn(Format('%.3f -- %.3f', [Start, Start + Duration]));
end;
end;
Vad.Flush;
while not Vad.IsEmpty do
begin
SetLength(AllSpeechSegment, Length(AllSpeechSegment) + 1);
SpeechSegment := Vad.Front();
Vad.Pop();
AllSpeechSegment[Length(AllSpeechSegment)-1] := SpeechSegment;
Start := SpeechSegment.Start / SampleRate;
Duration := Length(SpeechSegment.Samples) / SampleRate;
WriteLn(Format('%.3f -- %.3f', [Start, Start + Duration]));
end;
N := 0;
for SpeechSegment in AllSpeechSegment do
Inc(N, Length(SpeechSegment.Samples));
SetLength(AllSamples, N);
N := 0;
for SpeechSegment in AllSpeechSegment do
begin
for I := Low(SpeechSegment.Samples) to High(SpeechSegment.Samples) do
begin
AllSamples[N] := SpeechSegment.Samples[I];
Inc(N);
end;
end;
SherpaOnnxWriteWave('./lei-jun-test-no-silence.wav', AllSamples, SampleRate);
WriteLn('Saved to ./lei-jun-test-no-silence.wav');
FreeAndNil(Vad);
end.

34
pascal-api-examples/vad/run-circular-buffer.sh Executable file
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@@ -0,0 +1,34 @@
#!/usr/bin/env bash
set -ex
SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
SHERPA_ONNX_DIR=$(cd $SCRIPT_DIR/../.. && pwd)
echo "SHERPA_ONNX_DIR: $SHERPA_ONNX_DIR"
if [[ ! -f ../../build/install/lib/libsherpa-onnx-c-api.dylib && ! -f ../../build/install/lib/libsherpa-onnx-c-api.so && ! -f ../../build/install/lib/sherpa-onnx-c-api.dll ]]; then
mkdir -p ../../build
pushd ../../build
cmake \
-DCMAKE_INSTALL_PREFIX=./install \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
..
cmake --build . --target install --config Release
popd
fi
fpc \
-Fu$SHERPA_ONNX_DIR/sherpa-onnx/pascal-api \
-Fl$SHERPA_ONNX_DIR/build/install/lib \
./circular_buffer.pas
export LD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$LD_LIBRARY_PATH
export DYLD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$DYLD_LIBRARY_PATH
./circular_buffer

42
pascal-api-examples/vad/run-remove-silence.sh Executable file
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@@ -0,0 +1,42 @@
#!/usr/bin/env bash
set -ex
SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
SHERPA_ONNX_DIR=$(cd $SCRIPT_DIR/../.. && pwd)
echo "SHERPA_ONNX_DIR: $SHERPA_ONNX_DIR"
if [[ ! -f ../../build/install/lib/libsherpa-onnx-c-api.dylib && ! -f ../../build/install/lib/libsherpa-onnx-c-api.so && ! -f ../../build/install/lib/sherpa-onnx-c-api.dll ]]; then
mkdir -p ../../build
pushd ../../build
cmake \
-DCMAKE_INSTALL_PREFIX=./install \
-DSHERPA_ONNX_ENABLE_PYTHON=OFF \
-DSHERPA_ONNX_ENABLE_TESTS=OFF \
-DSHERPA_ONNX_ENABLE_CHECK=OFF \
-DBUILD_SHARED_LIBS=ON \
-DSHERPA_ONNX_ENABLE_PORTAUDIO=OFF \
..
cmake --build . --target install --config Release
popd
fi
if [[ ! -f ./silero_vad.onnx ]]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx
fi
if [ ! -f ./lei-jun-test.wav ]; then
curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/lei-jun-test.wav
fi
fpc \
-Fu$SHERPA_ONNX_DIR/sherpa-onnx/pascal-api \
-Fl$SHERPA_ONNX_DIR/build/install/lib \
./remove_silence.pas
export LD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$LD_LIBRARY_PATH
export DYLD_LIBRARY_PATH=$SHERPA_ONNX_DIR/build/install/lib:$DYLD_LIBRARY_PATH
./remove_silence