From 219c2482ab755fbd4e49dfbdee91bf1a8a4ec49a Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 19 五月 2023 11:33:27 +0800
Subject: [PATCH] websocket 2pass bugfix
---
funasr/runtime/onnxruntime/src/fsmn-vad.cpp | 26 ++++++++++++++++----------
1 files changed, 16 insertions(+), 10 deletions(-)
diff --git a/funasr/runtime/onnxruntime/src/fsmn-vad.cpp b/funasr/runtime/onnxruntime/src/fsmn-vad.cpp
index b1b0e63..516dc88 100644
--- a/funasr/runtime/onnxruntime/src/fsmn-vad.cpp
+++ b/funasr/runtime/onnxruntime/src/fsmn-vad.cpp
@@ -6,6 +6,7 @@
#include <fstream>
#include "precomp.h"
+namespace funasr {
void FsmnVad::InitVad(const std::string &vad_model, const std::string &vad_cmvn, const std::string &vad_config, int thread_num) {
session_options_.SetIntraOpNumThreads(thread_num);
session_options_.SetGraphOptimizationLevel(ORT_ENABLE_ALL);
@@ -161,17 +162,21 @@
}
// get 4 caches outputs,each size is 128*19
- for (int i = 1; i < 5; i++) {
- float* data = vad_ort_outputs[i].GetTensorMutableData<float>();
- memcpy(in_cache_[i-1].data(), data, sizeof(float) * 128*19);
- }
+ // for (int i = 1; i < 5; i++) {
+ // float* data = vad_ort_outputs[i].GetTensorMutableData<float>();
+ // memcpy(in_cache_[i-1].data(), data, sizeof(float) * 128*19);
+ // }
}
void FsmnVad::FbankKaldi(float sample_rate, std::vector<std::vector<float>> &vad_feats,
- const std::vector<float> &waves) {
+ std::vector<float> &waves) {
knf::OnlineFbank fbank(fbank_opts);
- fbank.AcceptWaveform(sample_rate, &waves[0], waves.size());
+ std::vector<float> buf(waves.size());
+ for (int32_t i = 0; i != waves.size(); ++i) {
+ buf[i] = waves[i] * 32768;
+ }
+ fbank.AcceptWaveform(sample_rate, buf.data(), buf.size());
int32_t frames = fbank.NumFramesReady();
for (int32_t i = 0; i != frames; ++i) {
const float *frame = fbank.GetFrame(i);
@@ -224,7 +229,7 @@
}
}
-std::vector<std::vector<float>> &FsmnVad::LfrCmvn(std::vector<std::vector<float>> &vad_feats) {
+void FsmnVad::LfrCmvn(std::vector<std::vector<float>> &vad_feats) {
std::vector<std::vector<float>> out_feats;
int T = vad_feats.size();
@@ -263,15 +268,14 @@
}
}
vad_feats = out_feats;
- return vad_feats;
}
std::vector<std::vector<int>>
-FsmnVad::Infer(const std::vector<float> &waves) {
+FsmnVad::Infer(std::vector<float> &waves, bool input_finished) {
std::vector<std::vector<float>> vad_feats;
std::vector<std::vector<float>> vad_probs;
FbankKaldi(vad_sample_rate_, vad_feats, waves);
- vad_feats = LfrCmvn(vad_feats);
+ LfrCmvn(vad_feats);
Forward(vad_feats, &vad_probs);
E2EVadModel vad_scorer = E2EVadModel();
@@ -301,3 +305,5 @@
FsmnVad::FsmnVad():env_(ORT_LOGGING_LEVEL_ERROR, ""),session_options_{} {
}
+
+} // namespace funasr
--
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