From b8825902d93d5017e44828316062dc8306b7ddcd Mon Sep 17 00:00:00 2001
From: Yabin Li <wucong.lyb@alibaba-inc.com>
Date: 星期二, 26 十二月 2023 10:51:00 +0800
Subject: [PATCH] support ngram and fst hotword for 2pass-offline (#1205)
---
runtime/websocket/bin/funasr-wss-server-2pass.cpp | 82 ++++++++++++++++++++++++++++++++++++++--
1 files changed, 77 insertions(+), 5 deletions(-)
diff --git a/runtime/websocket/bin/funasr-wss-server-2pass.cpp b/runtime/websocket/bin/funasr-wss-server-2pass.cpp
index 965f2a8..ef27d5b 100644
--- a/runtime/websocket/bin/funasr-wss-server-2pass.cpp
+++ b/runtime/websocket/bin/funasr-wss-server-2pass.cpp
@@ -16,6 +16,7 @@
// hotwords
std::unordered_map<std::string, int> hws_map_;
int fst_inc_wts_=20;
+float global_beam_, lattice_beam_, am_scale_;
using namespace std;
void GetValue(TCLAP::ValueArg<std::string>& value_arg, string key,
@@ -120,6 +121,14 @@
"connection",
false, "../../../ssl_key/server.key", "string");
+ TCLAP::ValueArg<float> global_beam("", GLOB_BEAM, "the decoding beam for beam searching ", false, 3.0, "float");
+ TCLAP::ValueArg<float> lattice_beam("", LAT_BEAM, "the lattice generation beam for beam searching ", false, 3.0, "float");
+ TCLAP::ValueArg<float> am_scale("", AM_SCALE, "the acoustic scale for beam searching ", false, 10.0, "float");
+
+ TCLAP::ValueArg<std::string> lm_dir("", LM_DIR,
+ "the LM model path, which contains compiled models: TLG.fst, config.yaml ", false, "damo/speech_ngram_lm_zh-cn-ai-wesp-fst", "string");
+ TCLAP::ValueArg<std::string> lm_revision(
+ "", "lm-revision", "LM model revision", false, "v1.0.2", "string");
TCLAP::ValueArg<std::string> hotword("", HOTWORD,
"the hotword file, one hotword perline, Format: Hotword Weight (could be: 闃块噷宸村反 20)",
false, "/workspace/resources/hotwords.txt", "string");
@@ -128,6 +137,10 @@
// add file
cmd.add(hotword);
+ cmd.add(fst_inc_wts);
+ cmd.add(global_beam);
+ cmd.add(lattice_beam);
+ cmd.add(am_scale);
cmd.add(certfile);
cmd.add(keyfile);
@@ -146,6 +159,8 @@
cmd.add(punc_quant);
cmd.add(itn_dir);
cmd.add(itn_revision);
+ cmd.add(lm_dir);
+ cmd.add(lm_revision);
cmd.add(listen_ip);
cmd.add(port);
@@ -163,6 +178,7 @@
GetValue(punc_dir, PUNC_DIR, model_path);
GetValue(punc_quant, PUNC_QUANT, model_path);
GetValue(itn_dir, ITN_DIR, model_path);
+ GetValue(lm_dir, LM_DIR, model_path);
GetValue(hotword, HOTWORD, model_path);
GetValue(offline_model_revision, "offline-model-revision", model_path);
@@ -170,6 +186,11 @@
GetValue(vad_revision, "vad-revision", model_path);
GetValue(punc_revision, "punc-revision", model_path);
GetValue(itn_revision, "itn-revision", model_path);
+ GetValue(lm_revision, "lm-revision", model_path);
+
+ global_beam_ = global_beam.getValue();
+ lattice_beam_ = lattice_beam.getValue();
+ am_scale_ = am_scale.getValue();
// Download model form Modelscope
try {
@@ -183,6 +204,7 @@
std::string s_punc_path = model_path[PUNC_DIR];
std::string s_punc_quant = model_path[PUNC_QUANT];
std::string s_itn_path = model_path[ITN_DIR];
+ std::string s_lm_path = model_path[LM_DIR];
std::string python_cmd =
"python -m funasr.utils.runtime_sdk_download_tool --type onnx --quantize True ";
@@ -241,11 +263,18 @@
size_t found = s_offline_asr_path.find("speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404");
if (found != std::string::npos) {
model_path["offline-model-revision"]="v1.2.4";
- } else{
- found = s_offline_asr_path.find("speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404");
- if (found != std::string::npos) {
- model_path["offline-model-revision"]="v1.0.5";
- }
+ }
+
+ found = s_offline_asr_path.find("speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404");
+ if (found != std::string::npos) {
+ model_path["offline-model-revision"]="v1.0.5";
+ }
+
+ found = s_offline_asr_path.find("speech_paraformer-large_asr_nat-en-16k-common-vocab10020");
+ if (found != std::string::npos) {
+ model_path["model-revision"]="v1.0.0";
+ s_itn_path="";
+ s_lm_path="";
}
if (access(s_offline_asr_path.c_str(), F_OK) == 0) {
@@ -332,6 +361,49 @@
LOG(INFO) << "ASR online model is not set, use default.";
}
+ if (!s_lm_path.empty() && s_lm_path != "NONE" && s_lm_path != "none") {
+ std::string python_cmd_lm;
+ std::string down_lm_path;
+ std::string down_lm_model;
+
+ if (access(s_lm_path.c_str(), F_OK) == 0) {
+ // local
+ python_cmd_lm = python_cmd + " --model-name " + s_lm_path +
+ " --export-dir ./ " + " --model_revision " +
+ model_path["lm-revision"] + " --export False ";
+ down_lm_path = s_lm_path;
+ } else {
+ // modelscope
+ LOG(INFO) << "Download model: " << s_lm_path
+ << " from modelscope : ";
+ python_cmd_lm = python_cmd + " --model-name " +
+ s_lm_path +
+ " --export-dir " + s_download_model_dir +
+ " --model_revision " + model_path["lm-revision"]
+ + " --export False ";
+ down_lm_path =
+ s_download_model_dir +
+ "/" + s_lm_path;
+ }
+
+ int ret = system(python_cmd_lm.c_str());
+ if (ret != 0) {
+ LOG(INFO) << "Failed to download model from modelscope. If you set local lm model path, you can ignore the errors.";
+ }
+ down_lm_model = down_lm_path + "/TLG.fst";
+
+ if (access(down_lm_model.c_str(), F_OK) != 0) {
+ LOG(ERROR) << down_lm_model << " do not exists.";
+ exit(-1);
+ } else {
+ model_path[LM_DIR] = down_lm_path;
+ LOG(INFO) << "Set " << LM_DIR << " : " << model_path[LM_DIR];
+ }
+ } else {
+ LOG(INFO) << "LM model is not set, not executed.";
+ model_path[LM_DIR] = "";
+ }
+
if (!s_punc_path.empty()) {
std::string python_cmd_punc;
std::string down_punc_path;
--
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