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PaddleSpeech/runtime/examples/vad/README.md

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[runtime] optimization compile and add vad interface (#3026) * vad recipe ok * refactor vad, add vad conf, vad inerface, vad recipe * format * install vad lib/bin/inc * using cpack * add vad doc, fix vad state name * add comment * refactor fastdeploy download * add vad jni; format code * add timer; compute vad rtf; vad add beam param * andorid find library * fix log; add vad rtf * fix glog * fix BUILD_TYPE bug * update doc * rm jni
2 years ago
# Silero VAD - pre-trained enterprise-grade Voice Activity Detector
This directory provides VAD models on CPU/GPU.
![](https://user-images.githubusercontent.com/36505480/198026365-8da383e0-5398-4a12-b7f8-22c2c0059512.png)
## VAD Interface
For vad interface please see [](../../engine/vad/interface/).
### Create Handdle
```c++
PPSHandle_t PPSVadCreateInstance(const char* conf_path);
```
### Destroy Handdle
```c++
int PPSVadDestroyInstance(PPSHandle_t instance);
```
### Reset Vad State
```c++
int PPSVadReset(PPSHandle_t instance);
```
Reset Vad state before processing next `wav`.
### Get Chunk Size
```c++
int PPSVadChunkSizeSamples(PPSHandle_t instance);
```
This API will return chunk size in `sample` unit.
When do forward, we need feed `chunk size` samples, except last chunk.
### Vad Forward
```c++
PPSVadState_t PPSVadFeedForward(PPSHandle_t instance,
float* chunk,
int num_element);
```
Vad has below states:
```c++
typedef enum {
PPS_VAD_ILLEGAL = 0, // error
PPS_VAD_SIL, // silence
PPS_VAD_START, // start speech
PPS_VAD_SPEECH, // in speech
PPS_VAD_END, // end speech
PPS_VAD_NUMSTATES, // number of states
} PPSVadState_t;
```
If `PPSVadFeedForward` occur an error will return `PPS_VAD_ILLEGAL` state.
## Linux
### Build Runtime
```bash
# cd /path/to/paddlespeech/runtime
cmake -B build -DBUILD_SHARED_LIBS=OFF -DWITH_ASR=OFF -DWITH_CLS=OFF -DWITH_VAD=ON
cmake --build build
```
Since VAD using FastDeploy runtime, if you have another FastDeploy Library, you can using this command to build:
```bash
# cd /path/to/paddlespeech/runtime
cmake -B build -DBUILD_SHARED_LIBS=OFF -DWITH_ASR=OFF -DWITH_CLS=OFF -DWITH_VAD=ON -DFASTDEPLOY_INSTALL_DIR=/workspace//paddle/FastDeploy/build/Linux/x86_64/install
cmake --build build
```
`DFASTDEPLOY_INSTALL_DIR` is the directory of FastDeploy Library.
### Run Demo
After building success, we can do this to run demo under this example dir:
```bash
bash run.sh
```
The output like these:
```bash
/workspace//PaddleSpeech/runtime/engine/vad/nnet/vad.cc(88)::SetConfig sr=16 threshold=0.5 beam=0.15 frame_ms=32 min_silence_duration_ms=200 speech_pad_left_ms=0 speech_pad_right_ms=0[INFO] fastdeploy/runtime/runtime.cc(293)::CreateOrtBackend Runtime initialized with Backend::ORT in Device::CPU./workspace//PaddleSpeech/runtime/engine/vad/nnet/vad.cc(137)::Initialize init done.[SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [STA] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [END] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [STA] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SIL] [SIL] [SIL] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [END] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [STA] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [END] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [STA] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SIL] [SIL] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SPE] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [END] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL] [SIL]
RTF=0.00774591
speak start: 0.32 s, end: 2.464 s | speak start: 3.296 s, end: 4.64 s | speak start: 5.408 s, end: 7.872 s | speak start: 8.192 s, end: 10.72 s
vad_nnet_main done!
sr = 16000
frame_ms = 32
threshold = 0.5
beam = 0.15
min_silence_duration_ms = 200
speech_pad_left_ms = 0
speech_pad_right_ms = 0
model_path = ./data/silero_vad/silero_vad.onnx
param_path = (default)num_cpu_thread = 1(default)/workspace//PaddleSpeech/runtime/engine/vad/nnet/vad.cc(88)::SetConfig sr=16 threshold=0.5 beam=0.15 frame_ms=32 min_silence_duration_ms=200 speech_pad_left_ms=0 speech_pad_right_ms=0[INFO] fastdeploy/runtime/runtime.cc(293)::CreateOrtBackend Runtime initialized with Backend::ORT in Device::CPU./workspace//PaddleSpeech/runtime/engine/vad/nnet/vad.cc(137)::Initialize init done.
1 1 1 1 1 1 1 1 1 1 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1 1 2 3 3 3 3 3 3 3 3 3 3 3 1 1 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1
RTF=0.00778218
vad_interface_main done!
```
## Android
When to using on Android, please setup your `NDK` enverment before, then do as below:
```bash
# cd /path/to/paddlespeech/runtime
bash build_android.sh
```
## Result
| Arch | RTF | Runtime Size |
|--|--|--|
| x86_64 | 0.00778218 | |
| arm64-v8a | 0.00744745 | ~10.532MB |
## Machine Information
#### x86_64
The environment as below:
```text
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 80
On-line CPU(s) list: 0-79
Thread(s) per core: 2
Core(s) per socket: 20
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Gold 6271C CPU @ 2.60GHz
Stepping: 7
CPU MHz: 2599.998
BogoMIPS: 5199.99
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 32K
L1i cache: 32K
L2 cache: 1024K
L3 cache: 33792K
NUMA node0 CPU(s): 0-39
NUMA node1 CPU(s): 40-79
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology nonstop_tsc eagerfpu pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 arat umip pku ospke avx512_vnni spec_ctrl arch_capabilities
```
#### arm64-v8a
```text
Processor : AArch64 Processor rev 14 (aarch64)
processor : 0
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x805
CPU revision : 14
processor : 1
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x805
CPU revision : 14
processor : 2
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x805
CPU revision : 14
processor : 3
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x805
CPU revision : 14
processor : 4
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x804
CPU revision : 14
processor : 5
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x804
CPU revision : 14
processor : 6
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x804
CPU revision : 14
processor : 7
BogoMIPS : 38.40
Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop
CPU implementer : 0x51
CPU architecture: 8
CPU variant : 0xd
CPU part : 0x804
CPU revision : 14
Hardware : Qualcomm Technologies, Inc SM8150
```
## Download Pre-trained ONNX Model
For developers' testing, model exported by VAD are provided below. Developers can download them directly.
| 模型 | 大小 | 备注 |
| :----------------------------------------------------------- | :---- | :----------------------------------------------------------- |
| [silero-vad](https://bj.bcebos.com/paddlehub/fastdeploy/silero_vad.tgz) | 1.8MB | This model file is sourced from [snakers4/silero-vad](https://github.com/snakers4/silero-vad)，MIT License |
## FastDeploy Runtime
For FastDeploy software and hardware requements, and pre-released library please to see [FastDeploy](https://github.com/PaddlePaddle/FastDeploy):
- 1. [FastDeploy Environment Requirements](https://github.com/PaddlePaddle/FastDeploy/docs/en/build_and_install/download_prebuilt_libraries.md).
- 2. [FastDeploy Precompiled Library](https://github.com/PaddlePaddle/FastDeploy/docs/en/build_and_install/download_prebuilt_libraries.md).
## Reference
* https://github.com/snakers4/silero-vad
* https://github.com/PaddlePaddle/FastDeploy/blob/develop/examples/audio/silero-vad/README.md